Skip to main content
BMC Genomics logoLink to BMC Genomics
. 2024 Dec 10;25:1186. doi: 10.1186/s12864-024-11077-5

Unveiling genetic insights: Array-CGH and WES discoveries in a cohort of 122 children with essential autism spectrum disorder

Paola Granata 1, Alessandra Zito 2, Dario Cocciadiferro 3, Antonio Novelli 3, Chiara Pessina 1, Tommaso Mazza 3,4, Matteo Ferri 5, Paolo Piccinelli 5, Chiara Luoni 5, Cristiano Termine 6, Mauro Fasano 7,8,, Rosario Casalone 1
PMCID: PMC11629504  PMID: 39654053

Abstract

Background

Autistic Spectrum Disorder (ASD) is a neurodevelopmental disorder with a strong genetic component and high heterogeneity. Essential ASD refers to patients who do not have other comorbidities. This study aimed to investigate the genetic basis of essential ASD using whole exome sequencing (WES) and array-comparative genomic hybridization (array-CGH).

Results

In a cohort of 122 children with essential ASD, WES detected 382 variants across 223 genes, while array-CGH identified 46 copy number variants (CNVs). The combined use of WES and array-CGH revealed pathogenic variants in four patients (3.1% detection rate) and likely pathogenic variants in 34 patients (27.8% detection rate). Only one patient had a pathogenic CNV (0.8% detection rate). Including likely pathogenic variants, the overall detection rate was 31.2%. Additionally, 33 de novo heterozygous sequence variants were identified by WES, with three classified as pathogenic and 13 as likely pathogenic. Sequence variants were found in 85 genes already associated with ASD, and 138 genes not previously included in the SFARI dataset were identified as potential new candidate genes.

Conclusions

The study enhances genetic understanding of essential ASD and identifies new candidate genes of interest. The findings suggest that using both array-CGH and WES in patients with essential ASD can improve the detection of pathogenic and likely pathogenic genetic variants, contributing to better diagnosis and potentially guiding future research and treatment strategies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-024-11077-5.

Keywords: Essential autistic spectrum disorder, ASD, Array-comparative genomic hybridization (array-CGH), Copy number variants (CNVs)

Background

Autistic Spectrum Disorder (ASD) includes a diverse group of neurodevelopmental disorders characterized by deficits in social communication and interaction, along with restricted and repetitive behaviors, interests, and activities. The prevalence of ASD in the general population is approximately 1%. Many patients with ASD also exhibit global developmental delay (GDD) and epilepsy, leading to the classification of “complex ASD”. Other patients may have specific patterns of abnormalities or dysmorphic features, referred to as “syndromic ASD”, which includes conditions like Fragile X syndrome, Rett syndrome, Down’s Syndrome, Phenylketonuria, Angelman syndrome, and Tuberous Sclerosis Complex [13]. Non-syndromic ASD refers to patients without dysmorphic traits, comorbidities, or a characteristic symptom pattern of a specific syndrome. ASD can be categorized into three subtypes: essential ASD (three or fewer anomalies), equivocal ASD (four or five anomalies), and complex ASD (six or more anomalies) [3]. Males are more frequently affected than females, with a male-to-female ratio of 2.5:1 for complex ASD [4] and 4.5:1 for essential ASD [5].

Array-comparative genomic hybridization (array-CGH) has been integrated into genetic diagnostics for ASD, identifying copy number variations (CNVs) that contribute to approximately 10% of ASD cases [6]. Variants of uncertain significance (VOUS) are also frequently identified, with de novo CNVs present in about 4% of ASD patients [7]. CNVs related to neuronal cell adhesion, ubiquitin pathways [8], and postsynaptic cell adhesion [9] are biologically associated with ASD. The Simons Foundation Autism Research Initiative (SFARI) database lists recurrent CNVs associated with ASD [10]. Previous studies on array-CGH in essential ASD have shown a causative CNV detection rate (DR) of 9%, with no significant difference in cognitive abilities among groups with and without causative CNVs [11]. However, a higher number of non-verbal children were observed in the causative CNV group. High-resolution array-CGH findings in essential ASD have reported lower frequencies of pathogenic CNVs compared to complex ASD, with no correlation between genetic results and clinical aspects. In high-functioning autism (HFA) without epilepsy, intellectual disability, or known genetic diseases, array-CGH identified CNVs containing brain-related genes but found no difference in the number of CNVs compared to random population samples [12]. In non-syndromic autism with epilepsy, intellectual disability, and ADHD, array-CGH identified de novo pathogenic CNVs in 6.25% of patients [13] .

Next-generation sequencing techniques, such as whole exome sequencing (WES) and whole genome sequencing (WGS), have identified hundreds of gene variants involved in ASD, highlighting the role of de novo sequence variants [14, 15]. A combination of WES and array-CGH in essential ASD has identified clinically significant variants in 5.9% of cases, with pathogenic CNVs found in 4.2% and WES-positive findings in 3.1% of essential ASD patients [13, 16]. Interestingly, while hundreds of ASD loci have been identified, the genetic basis of ASD remains elusive, and only a small fraction of ASD patients have been associated with specific genetic variants. Other factors, such as rare genetic variations, epigenetic changes, gene-gene interactions, or environmental factors, may also play a role in the development of ASD, highlighting the need for continued research to better understand the genetic and non-genetic factors that contribute to the disease.

In this study, we analyzed 122 children with essential ASD and their parents using array-CGH and WES. We report the molecular findings from this dual testing strategy and discuss the potential pathogenicity and clinical significance of the results.

Methods

Participants

We enrolled 122 patients (104 males and 18 females) with a diagnosis of essential ASD. These patients had no epilepsy, dysmorphic features, intellectual disability, microcephaly, six or more minor anomalies, or systemic congenital malformations such as congenital heart defects. Patients were recruited from the Child Neuropsychiatry Unit and the Cytogenetics and Medical Genetics Unit of “ASST Sette Laghi”, Varese, Italy. A clinical geneticist assessed heritability for neuropsychiatric disorders and neurodevelopmental diseases and excluded multiple congenital abnormalities, malformations, or syndromes. Subjects aged from three to 12 years, with an ASD diagnosis based on DSM-5 criteria, were included. Exclusion criteria were: (a) demonstrated syndromic ASD with a genetic basis or up to six other clinical features (complex ASD); (b) absence of one or both parents; (c) known syndromes related to specific genetic causes; (d) presence of epilepsy or use of epileptic pharmacological therapy, or febrile seizures within six months prior to medical counseling; (e) other psychopharmacological therapies. Written informed consent for genetic and clinical ASD tests and the use of biological results for research in an anonymous form was provided by the parents and relatives of the probands. The consent model and procedure were approved by the Institutional Review Board (“ASST Sette Laghi” Code MOD09 IOS01SSDGM).

Genetic investigation

DNA from peripheral blood cells has been selected as elective tissue for the genetic investigations. As a matter of fact, even if limited tissue mosaicism has been associated to syndromic neurodevelopmental disorders, it has not been confirmed in ASD affected patients [17, 18].

To identify submicroscopic chromosomal rearrangements, array-CGH technology was performed after DNA extraction from peripheral blood cells (QIAmp DNA Blood Maxi Kit, Qiagen, Hilden, Germany). The array-based comparative genomic hybridization was performed using the CytoSure ISCA V3 4 × 180 K platform, with a backbone resolution of 1 probe/22 Kb for high-priority backbone, 1 probe/24 Kb for medium-priority backbone, and 1 probe/54 Kb for low-priority backbone, using the human genome reference GRCh37/hg19 and sex-matched normal human DNA pool (Kreatech, Amsterdam, Holland) as control. The InnoScan 710 Microarray Scanner (Carbonne, France) and Mapix (Innopsys, Carbonne, France) were used to detect and analyze fluorescence levels. Results were interpreted using Cytosure Interpret Software (Oxford Gene Technology, Begbroke, Oxfordshire, United Kingdom). QC metrics required were SD < 1.0 and DLR spread < 0.3.

Whole exome sequencing

WES was performed in trios using the Twist Human Core Exome Kit (Twist Bioscience, San Francisco, USA) according to the manufacturer’s protocol and sequenced with the Illumina NovaSeq 6000 platform. The BaseSpace pipeline (Illumina, San Diego, USA) and TGex software (LifeMap Sciences, Alameda, USA) were used for variant calling and annotation, respectively. Sequencing data were aligned to the GRCh37/hg19 human reference genome. Variants with a coverage lower than 10×, quality score (GQ) lower than 15, and gnomAD minor allele frequency (MAF) lower than 5% were excluded. WES results were interpreted according to ACMG guidelines [19]. The prediction of the effect of a single base variant on protein structure and functionality was determined by the CADD score, using genome build GRCh37/hg19 v1.4 as reference. Annotations were performed using gnomAD, GeneCards, UniProtKB/Swiss-Prot, OMIM, GTEx, SFARI, CADD, and HGNC databases.

Gene filtering

WES was used to investigate 825 neurodevelopmental genes from the SFARI database (2018 Q3 version). Additionally, all other genes, whether included in the OMIM database or not, and not reported in the SFARI database, were considered if the analytic software detected de novo, compound heterozygous, truncating, frameshift, or splicing variants with MAF less than 1% in the general population (gnomAD database v2.1.1 and v3.1).

Sequence variant filtering

All synonymous variants and inherited heterozygous variants were excluded. Hemizygous, homozygous, compound heterozygous, and de novo variants with ≤ 10 homozygotes in the general population or not annotated in the gnomAD database (v2.1.1 and v3.1) were considered. Additionally, compound heterozygous variants were included if one variant was classified as likely pathogenic (LP) and the second variant was classified as variant of uncertain significance (VOUS), LP, or pathogenic (P), regardless of the number of homozygotes in population databases.

Pathogenic evaluation criteria of sequence variants

Variants were classified as likely benign (LB), VOUS, LP, or P according to the following criteria:

Variants in SFARI genes were classified as P if they had a CADD score ≥ 20 (criterion 1), an ACMG evaluation of P or LP (criterion 2), and were not found in the gnomAD database or had zero or one homozygote in the general population (criterion 3).

A variant was considered LP if it had two to ten homozygous subjects in the general population and satisfied criterion 1, with ACMG evaluation of P, LP, or VOUS, and involvement in neurodevelopment, nervous system function, synaptic transmission, or epigenetic transcription regulation (criterion 4).

Variants with a CADD score < 15 and ACMG evaluation of LB were classified as LB or B.

Variants not meeting these criteria were classified as VOUS.

For genes not in the SFARI database, variants were classified as LP if they met criteria 1, 2, and 4. They were classified as LB or B with ACMG evaluation of B, LB, or VOUS and a CADD score < 15. Variants in non-SFARI genes were conservatively not classified as P due to their unknown implication in the ASD phenotype.

Compound heterozygous conditions were defined by considering the combination of the pathogenicity classification of single variants as shown in Table 1.

Table 1.

Classification of compound heterozygosity conditions

Variant 1 Variant 2 Classification
P P or LP P
LP LP or VOUS LP
VOUS LB or VOUS VOUS
LB LP or P VOUS
LB LB LB

Considering that most variants in neurodevelopmental disorders are susceptibility factors with incomplete penetrance [20, 21], we considered incomplete penetrance for variants found in all patients to determine their pathogenicity.

Copy number variants (CNVs) interpretation and classification

CNVs were interpreted using public databases like DECIPHER (including dosage sensitivity scores and sampling probability) and the Database for Genetic Variants (DGV). Classification followed the American College of Medical Genetics (ACMG) Joint Consensus [22] and Cytogenetic European and International Guidelines [23], categorizing CNVs as P, LP, VOUS, LB, or B. CNVs classified as B or LB and those present in more than 1% of healthy subjects in the DGV database were excluded.

Criteria for “Genes of interest” definition in CNVs

Genes involved in monogenic CNVs were considered of interest. In multiple-gene CNVs, candidate genes were selected based on SFARI score, function, involvement in neurodevelopment, brain expression levels (TGEx), and dosage sensitivity.

Data processing

All WES and array-CGH data were analyzed considering variant effects, pathogenicity classification, zygosity, recurrence, and gene families identified via GeneCards [24]. Non-annotated variants in the gnomAD database and genes not reported in SFARI were emphasized. Detection rates for the two combined tests in the 122 patients with Essential Autism were estimated based on P and LP variants.

Selection of genes for gene families

Gene families with more than five genes were analyzed. Genes that were recurrent and not annotated in the SFARI database were considered. Family identification and selection were performed using information from GeneCards (genecards.com) and UniProt (uniprot.com).

Results

Genetic analysis of DNA samples extracted from blood tissue of 122 ASD subjects revealed a positive result for a genetic variant based on variant calling exclusively from WES in 74 samples, while 30 showed positive results from both WES and array-CGH.

Five individuals tested positive only on array-CGH, and 13 had negative results on genetic testing. The cohort consisted of 104 males and 18 females, resulting in a male-to-female ratio of 5.8:1. Descriptive statistics and detection rates are reported in Table 2, compared with previous studies.

Table 2.

Detection rates of sequence and copy number variants

Category This study Other Studies
Pathogenic variants 3.3% (4 cases) 5.9% (25) 6.3% (16)
- Pathogenic sequence variants 2.5% (3 cases) 3.1% (16)
- Pathogenic CNVs 0.82% (1 case) 3.1% (11), 9% (2), 4.2% (16)
Likely Pathogenic (LP) variants 27.9% (34 cases)
- LP sequence variants 19.7% (24 cases)
- LP CNVs 6.5% (8 cases)
- LP sequence variants & CNVs 1.6% (2 cases)
Variants of Uncertain Significance (VOUS) 57.4% (70 cases)
- VOUS sequence variants 44.3% (54 cases)
- VOUS CNVs 2.5% (3 cases)
- VOUS sequence variants & CNVs 10.6% (13 cases)
No variants or benign/likely benign 11.5% (14 cases)
Overall Detection Rate with LP variants 30.8% (32 cases)

A total of 381 sequence variants across 223 genes were identified in 104 patients using Whole Exome Sequencing (WES), including 317 non-synonymous missense variants, 16 frameshift, seven indels, 32 splicing variants, four start codon changes, and five stop codon changes (see Supplementary Table 1). Table 3 reports a summary of WES data.

Table 3.

Summary of sequence variants identified by WES

Category Number of Variants
Total Variants Identified (WES) 381
- Non-synonymous Missense 317
- Frameshift 16
- Indels 7
- Splicing Variants 32
- Start Codon Changes 4
- Stop Codon Changes 5
Classification of Variants
- Pathogenic 4
- Likely Pathogenic (LP) 34
- Variants of Uncertain Significance (VOUS) 289
- Likely Benign (LB) 54
de novo Heterozygous Variants 33 variants (28 cases)
- Pathogenic 3
- Likely Pathogenic (LP) 13
- Variants of Uncertain Significance (VOUS) 17
Hemizygous Variants 91 variants (56 cases)
- Likely Pathogenic (LP) 10
- Variants of Uncertain Significance (VOUS) 66
- Likely Benign (LB) 15
Homozygous Variants 14 variants (10 cases)
- Likely Pathogenic (LP) 2
- Variants of Uncertain Significance (VOUS) 12
- Likely Benign (LB) 1
Compound Heterozygous Variants 240 variants (70 cases)
- Pathogenic 1
- Likely Pathogenic (LP) 6
- Variants of Uncertain Significance (VOUS) 102
- Likely Benign (LB) 10
Private Variants (Unique) 95 variants (61 patients)
- Pathogenic 2 (2.1%)
- Likely Pathogenic (LP) 24 (25.3%)
- Variants of Uncertain Significance (VOUS) 61 (64.2%)
- Likely Benign (LB) 8 (8.4%)

Moreover, 46 CNVs were detected in 36 patients (see Supplementary Table 2). A summary of these variants is shown in Table 4. Combining the 259 genes with selected variants detected across both genetic tests, 32 gene families were represented (see Table 5).

Table 4.

Summary of copy number variants identified by aCGH

CNV Type Total Variants (%)
Deletions 16 (34.8%)
Duplications 30 (65.2%)
Pathogenic/Likely Pathogenic 12 (9.8%)
VOUS 34 (73.9%)

Table 5.

Gene families highlight. Gene families were selected from Uniprot/Swissprot and HGNC database

Patient Gene name Gene families Annotatation in SFARI db Number of genes
A070 ABCA13 ABC transporter superfamily YES 4
A111 ABCA13 YES
A115 ABCB7 NO
A016 ABCC1 NO
A016 ABCC6 NO
A013 SLC12A3 NO 3
A060 SLC25A6 NO
A008 SLC35A2 NO
A026 ACTL9 actin family NO 2
A076 ACTR5 actin family NO
A124 ACAD10 acyl-CoA dehydrogenase family NO 2
A060 ACAD8 NO
A116 ANK3 Ankyrin family YES 2
A052 ANK2 YES
A005 FAT1 Cadherin related YES 2
A044 FAT1 YES
A033 PCDH15 YES
A025 CDH13 cadherins Major YES 1
A114 CDH22 cadherins Type II classical YES 2
A017 CDH8 YES
A010 CACNA1F calcium channel alpha-1 subunit (TC 1.A.1.11) family YES 3
A107 CACNA1F YES
A011 CACNA1G YES
A029 CACNA2D1 calcium channel subunit alpha-2/delta family YES 1
A121 SCN2A sodium channel (TC 1.A.1.10) family YES 2
A046 SCN9A YES
A124 MAPKAPK5 protein kinase family CAMK Ser/Thr NO 3
A084 PASK YES
A080 PNCK NO
A028 MAP3K15 protein kinase family STE Ser/Thr NO 3
A099 PAK2 YES
A130 PAK3 NO
A084 COL16A1 Collagens family NO 2
A027 COL4A6 NO
A122 SEC24B COPII coat complex NO 2
A024 SEC31B NO
A079 DDX20 helicase family DEAD box NO 3
A060 DDX53 YES
A131 DDX53 YES
A125 DHX8 NO
A006 DHX8 NO
A003 ATRX helicase family SNF2/RAD54 YES 5
A050 CHD1L NO
A048 CHD7 YES
A075 EP400 YES
A034 EP400 YES
A103 EP400 YES
A109 EP400 YES
A079 SMARCA1 NO
A110 GPR50 G-protein coupled receptor 1 family NO 4
A003 HTR2A NO
A026 OR2Z1 NO
A060 P2RY8 NO
A108 CASR G-protein coupled receptor 3 family NO 2
A118 GABBR1 NO
A075 KIF13B Kinesin family YES 2
A074 KIF15 NO
A051 LRP1 LDLR family YES 2
A021 LRP2 YES
A120 LRP2 YES
A006 MAGEC1 MAGE family NO 2
A057 MAGEE2 NO
A058 MAGEE2 NO
A059 MAGEE2 NO
A060 MAP7D2 MAP7 family NO 2
A026 MAP7D3 NO
A011 NRXN1 neurexin family YES 2
A120 NRXN3 YES
A093 PLXNA3 plexin family YES 2
A099 PLXNA3 YES
A010 PLXNB3 NO
A016 MARF1 Protein phosphatase 1 regulatory subunits NO 3
A025 PREX2 NO
A021 YLPM1 NO
A002 PPP2R1B Protein phosphatase 2 regulatory subunits YES 2
A097 PPP2R3B NO
A014 PTPRB protein-tyrosine phosphatase family YES 2
Z008 PTPRF NO
A062 RNF19A Ring finger proteins NO 3
A097 RNF220 NO
A100 RNF25 YES
A065 TRIM32 TRIM/RBCC family YES 2
A095 TRIM35 NO
A088 CRLF2 cytokine receptor type I family- NO 2
A119 CRLF2 NO
A060 IL3RA NO
A095 VCX VCX/VCY family NO 2
A084 VCX3B NO
A111 LLGL1 WD repeat L(2)GL family NO 2
A071 STXBP5 YES
A014 HIVEP2 Zinc fingers C2H2-type family YES 11
A044 HIVEP3 YES
A008 KLF8 NO
A029 PRDM15 NO
A026 ZHX1 NO
A020 ZIC1 NO
A020 ZIC4 NO
A125 ZNF462 YES
A027 ZNF630 YES
A051 ZSCAN21 NO
A006 ZMYM2 Zinc fingers MYM-type family NO 3
A006 ZMYM5 NO
A113 ZMYM5 NO
A093 SMYD1 NO

Discussion

Detection rate

The overall detection rate (DR) of 3.3% for pathogenic variants in this cohort matches prior findings but is lower compared to some studies [2, 11, 16, 25]. The disparity in DR between different studies may be attributed to varying classification criteria and testing methodologies. When likely pathogenic variants (LP) are included, the detection rate increased substantially to 30.8%, reflecting the potential clinical relevance of LP variants in understanding ASD etiology. P or LP variants were found in patients A013, A016, A017, A022, A037, A041, A044, A050, A052, A054, A065, A075, A076, A078, A080, A082, A088, A096, A097, A100, A102, A105, A108, A110, A112, A118, A120, A121, A124, A125, A130 and A132.

Whole exome sequence variants

A total of 381 variants were identified using WES, as summarized in Table 2. A summary of genes showing variants observed here is reported in Table 6.

Table 6.

Summary of genes showing sequence variants

Gene Variant
(HGVS Coding)
Patients Zygosity Gene Function GO Terms Known ASD Gene (SFARI) CADD Score
AKAP9 c.506 C > T A013 Homozygous, Compound Heterozygous Anchoring protein for PKA, regulates signaling pathways GO:0005515 (protein binding), GO:0000165 (MAPK cascade) Yes 29.3
ABCA13 c.4779_4780insGCGC A052, A068 Compound Heterozygous Involved in lipid transport and possibly neurological function GO:0006810 (transport), GO:0030301 (cholesterol transport) Yes 23.4
AGBL4 c.101G > T, c.-41 C > T A071, A072, A073 Compound Heterozygous Tubulin deglutamylase, involved in axonal transport and neuron development GO:0098957 (anterograde axonal transport), GO:0021954 (CNS neuron development) Yes 24.6, 11.7
CIC c.1795 C > T A070, A076 Compound Heterozygous, De novo Transcriptional repressor involved in cell growth and development GO:0003677 (DNA binding), GO:0045892 (negative regulation of transcription) Yes 13.9
DST c.2689 A > C A052, A075 Compound Heterozygous Cytoskeletal linker protein, critical for maintaining the structure of neural and epithelial cells GO:0008092 (cytoskeletal protein binding), GO:0030155 (regulation of cell adhesion) Yes 17.4
EP400 c.916 A > G A110 Homozygous, Compound Heterozygous Component of chromatin remodeling complex, involved in DNA repair and gene regulation GO:0006338 (chromatin remodeling), GO:0006281 (DNA repair) Yes 31.0
EPPK1 c.5101G > A A038, A068 Compound Heterozygous Cytoskeletal linker protein, involved in cytoskeletal architecture GO:0005856 (cytoskeletal architecture) No 24.8
FAT1 c.1505 A > G A075 Compound Heterozygous Cadherin involved in cell adhesion and cytoskeleton organization GO:0007155 (cell adhesion), GO:0009897 (external side of plasma membrane) Yes 13.2
IL1RAPL1 c.1507G > A A118 Hemizygous Involved in synapse formation and immune response regulation GO:0006955 (immune response), GO:0050808 (synapse organization) Yes 3.7
KDM6B c.1415 A > G A100, A102 Compound Heterozygous Histone demethylase involved in gene expression and developmental processes GO:0034720 (histone demethylation), GO:0045893 (positive regulation of transcription) Yes 24.3
LRP2 c.682 C > A A072 Compound Heterozygous Multi-ligand endocytic receptor, involved in transport of nutrients and signaling molecules GO:0005041 (low-density lipoprotein receptor activity), GO:0034389 (lipid transport) Yes 34.0
MAGEE2 c.181G > A A057, A058, A059 Hemizygous Negative regulation of transcription by RNA polymerase II GO:0000122 (negative regulation of transcription) No 8.5
NEXMIF c.700G > A A044 Hemizygous Involved in synaptic plasticity, learning, and memory GO:0007399 (nervous system development), GO:0050890 (cognition) Yes 22.9
SYN1 c.926G > A A071 Hemizygous Synapsin, involved in neurotransmitter release at synapses GO:0007268 (synaptic transmission), GO:0007269 (neurotransmitter secretion) Yes 10.9
SYNE1 c.1697 A > G A096 Compound Heterozygous, De novo Involved in nuclear anchoring and structural organization of the cytoskeleton GO:0015629 (actin cytoskeleton), GO:0005884 (intermediate filament) Yes 15.4
TAF6 c.14,185 C > T A041 Homozygous, Compound Heterozygous General transcription factor, part of TFIID complex involved in RNA polymerase II transcription GO:0006366 (transcription from RNA polymerase II promoter), GO:0016607 (nuclear speck) Yes 24.3
KCND1 c.1373G > A A020 Hemizygous Voltage-gated A-type potassium channel; membrane repolarization GO:0005249 (voltage-gated potassium channel activity), GO:0071805 (potassium ion transport) No 20.1
PDE4DIP c.907G > C A052, A094 Compound Heterozygous Involved in microtubule assembly, Golgi apparatus organization, cell migration GO:0030953 (microtubule assembly), GO:1,903,358 (Golgi apparatus organization), GO:0007098 (centrosome cycle) No 20.2
HMCN2 c.2110 C > A A075 Compound Heterozygous Involved in synapse formation and neuronal development GO:0007165 (signal transduction), GO:0035238 (neuron development) Yes 18.5
HIVEP3 c.181G > A A072 Hemizygous Transcriptional activator involved in cell differentiation and proliferation GO:0006355 (regulation of transcription), GO:0045664 (neuron differentiation) No 15.8
KIF13B c.126G > C A071, A076 Compound Heterozygous Motor protein involved in vesicular transport GO:0030814 (vesicle-mediated transport), GO:0006886 (vesicle transport) Yes 22.9
RANBP17 c.3045G > A A037 Hemizygous Involved in nuclear-cytoplasmic transport GO:0006913 (nuclear transport), GO:0006606 (nuclear import) Yes 19.3
TAF1 c.181G > A A100 Compound Heterozygous Transcription factor involved in the regulation of gene expression GO:0006355 (regulation of transcription), GO:0000122 (negative regulation of transcription) Yes 12.7
ZNF462 c.1903G > A A063, A066 Compound Heterozygous Zinc finger protein involved in transcription regulation GO:0003677 (DNA binding), GO:0006396 (RNA processing) No 25.5

Within the 317 non-synonymous coding variants, four were recurrent. For instance, the maternal hemizygous variant c.181G > A in the intronless gene MAGEE2 was present in three siblings (A057, A058, A059). This variant was classified as VOUS (CADD score of 8.5). It is worthy of note that this variant is the unique recurrent variant among our cohort and segregates in the family (it is present in the mother and the maternal grandfather who showed autistic traits). MAGEE2 encodes a member of the E subfamily of MAGE (melanoma antigen-encoding gene) family involved in the negative regulation of transcription by RNA polymerase II biological process (GO:0000122). Siblings A071, A072, and A073 carried two variants in compound heterozygosity in the AGBL4 gene: c.101G > T (CADD score = 24.6) and c.41 C > T (CADD score = 11.7). Both variants were inherited from healthy parents. AGBL4 is involved in biological processes such as anterograde and retrograde axonal transport of mitochondria (GO:0098957) and central nervous system neuron development (GO:0021954). Variant c.5101G > A in the EPPK1 gene is recurrent in compound heterozygosity in two unrelated patients (A038 and A068). The encoded protein is involved in the organization of cytoskeletal architecture (GO:0005856).

Sequence variants were identified in 223 genes. Among them, 85 genes were already known to be associated with ASD in the SFARI database. Actually, 20 genes were recurrent (ABCA13, AGBL4, AKAP9, CACNA1F, CDKL5, CIC, DDX53, DST, EP400, EPPK1, FAT1, IL1RAPL1, KDM6B, LRP2, NEXMIF, PLXNA3, PTK7, SYN1, SYNE1 and TAF6) and 138 genes were not included (six genes were recurrent: KCND1, LOC101059915, MAGEE2, PDE4DIP, SOX3 and SYTL4). Therefore, a total of 27 genes were recurrent (see Table 6) and showed different zygosities among patients. Recurrent genes with homozygous variants were AKAP9, EP400, LRP2, PTK7 and TAF6. ABCA13, AGBL4, CIC, DST, EP400, EPPK1, FAT1, KDM6B, PDE4DIP, PTK7 and SYNE1 showed variants in compound heterozygosity. Hemizygous variants were observed in CACNA1F, CDKL5, DDX53, IL1RAPL1, KCND1, LOC101059915, MAGEE2, NEXMIF, PLXNA3, SOX3, SYN1 and SYTL4. Eventually, recurrent genes showing de novo heterozygous variants were AKAP9, CIC, LRP2, SYNE1 and TAF6. Genes KCND1 and PDE4DIP were noteworthy because of their function related to nervous system development or functional regulation, and the MAGEE2 gene, since the variant was also present in other affected family members. KCND1 showed two different hemizygous private variants in two patients: the splice site region variant c.1368 + 1G > A was found in patient A132 as its unique candidate variant and was classified as LP; the second variant is c.1373G > A in patient A020, classified as LB. The gene KCND1 encodes a component of a membrane voltage-gated A-type potassium channel necessary for membrane repolarization. The activity of voltage-gated potassium channels (GO:0005249) is important in physiological processes such as the regulation of neurotransmitter release, heart rate, insulin secretion, and smooth muscle contraction and the gene provides potassium ions transmembrane transport (GO:0071805) and monoatomic ions transmembrane passage regulation (GO:0034765). PDE4DIP showed the compound heterozygous VOUS variants c.907G > C and c.6905 A > T in patient A052 and c.1546 C > T and c.5341 C > T in A094. PDE4DIP encodes a protein involved in microtubule assembly and nucleation (GO:0030953- GO:0090063), in the regulation of Golgi apparatus organization (GO:1903358) and in the centrosome cycle (GO:0007098), contributing to cell migration, mitotic spindle orientation and cell-cycle progression. Moreover, A052 showed two additional variants in compound heterozygosity: c.2380G > A and c.1399G > C in the HMCN2 gene encoding a protein with involvement in cell adhesion mediated by integrins (GO:0007155) and hemostasis regulation (GO:1900047). The variant c.2380G > A has been classified as LP and c.1399G > C as LB. Patient A094 showed a second compound heterozygosity in the TRPM2 gene: c.52G > A and c.4654G > A, both classified as LB. TRPM2 is a non-specific cation channel that mediates calcium influx (GO:0005262).

Ninety-five private variants (i.e., unique variants) in 89 genes were identified in 61 patients. Among them, two were pathogenic (2.1% in the sample of private variants), 24 LP (25.3%), 61 VOUS (64.2%), and eight likely benign (8.4%). Among the identified private pathogenic variants, A132 showed the hemizygous c.1368 + 1G > A variant in the KCND1 gene, inherited from his healthy mother, as its unique selected candidate variant. This variant is a splice site alteration with predicted loss of function of the gene product. It has been classified as LP (CADD score = 34), but, considering that it is the only genetic candidate and the presence of neurodevelopmental phenotypes in other patients with variants in the KCND1 gene, it can be classified as pathogenic. The gene product is part of the voltage-gated A-type potassium channels (GO:0034765) and has functional relevance for potassium ions transmembrane transport (GO:0071805) in neurons and for the regulation of neurotransmitter release and membrane repolarization after action potential. The gene has already been included in the SFARI genes database as 2B gene (Strong candidate). The remaining 24 LP variants are mostly compound heterozygous, with three homozygous variants, two de novo heterozygous and two hemizygous.

Copy number variants

A short summary of CNVs observed here is reported in Tables 3 and 7. Parental transmission was equally distributed between paternal and maternal sources.

Table 7.

Copy number variants, classification, encompassed genes and rearrangement

CNV - ISCN 2020 Inheritance Size CNV classification Genes Genes of Interest SFARI Score Type of gene rearrangement
13q14.13q14.2(47240527_48096722)x1 pat 856.2 kb VOUS LRCH1 INT START
ESD DELETED
HTR2A HTR2A DELETED
13q12.11(20146801_20270834)x3 pat 124.03 kb VOUS MPHOSPH8 MPHOSPH8 DUPLICATED
PSPC1 INT END
13q12.11(20411945_20559030)x3 pat 147.09 kb VOUS ZMYM5 ZMYM5 INT START
ZMYM2 ZMYM2 S INT END
17q21.31(41409849_41597925)x3 mat 188.08 kb VOUS DHX8 DHX8 INT END
7q11.22(69168540_69198438)x1 mat 29.9 kb LP AUTS2 AUTS2 1 INTRAGENIC
16p13.11(14968878_16311041)x1 de novo 1.34 Mb LP NOMO1 INT START
NPIPA1 DELETED
PDXDC1 DELETED
NTAN1 DELETED
RRN3 DELETED
MPV17L DELETED
MARF1 DELETED
NDE1 NDE1 DELETED
MYH11 DELETED
FOPNL DELETED
ABCC1 DELETED
ABCC6 INT END
16q21(60064996_63555913)x1 mat 3.49 Mb LP CDH8 CDH8 2 DELETED
3q24(147111840_147118109)x3 de novo 8.91 kb VOUS ZIC1 ZIC1 INTRAGENIC
ZIC4 INTRAGENIC
15q13.1(29656854_29783953)x1 pat 127.1 kb VOUS FAM189A1 FAM189A1 INTRAGENIC
Xp22.33(426261_679415)x2 mat 253.16 kb LP SHOX SHOX 2 DUPLICATED
16q23.3(82184809_83663330)x3 mat 1.48 Mb VOUS CDH13 CDH13 2 INT END
MPHOSPH6 INT START
7q21.11(81472446_81639364)x3 pat 166.92 kb VOUS CACNA2D1 CACNA2D1 2 INT END
16q23.2(80751184_80928051)x1 mat 176.87 kb VOUS CDYL2 CDYL2 INT START
Xq21.1(77081624_77139044)x2 mat 57.42 kb VOUS MAGT1 MAGT1 INT END
1q21.1q21.2(146542653_147872312)x1 pat 1.33 Mb LP PRKAB2 DELETED
FMO5 DELETED
BCL9 DELETED
CHD1L DELETED
ACP6 DELETED
GJA5 DELETED
GJA8 DELETED
GPR89B DELETED
1q21.1q21.2(146499008_147860611)x3 pat 1.36 Mb LP PRKAB2 DUPLICATED
FMO5 DUPLICATED
BCL9 DUPLICATED
CHD1L DUPLICATED
ACP6 DUPLICATED
GJA5 DUPLICATED
GJA8 DUPLICATED
GPR89B DUPLICATED
6q22.31(124068036_124449980)x3 mat 382 kb VOUS NKAIN2 NKAIN2 INT END
11q25(133124721_134353783)x3 mat 1.23 Mb VOUS OPCML INT START
SPATA19 DUPLICATED
IGSF9B DUPLICATED
JAM3 DUPLICATED
NCAPD3 DUPLICATED
VPS26B DUPLICATED
THYN1 DUPLICATED
ACAD8 DUPLICATED
B3GAT1 DUPLICATED
Yp11.32(1421350_1634267)x2 pat 212.9 kb VOUS IL3RA INT START
SLC25A6 DUPLICATED
ASMTL DUPLICATED
P2RY8 DUPLICATED
9q33.1(119387004_119527204)x1 mat 140.2 kb LP TRIM32 TRIM32 3 DELETED
ASTN2 ASTN2 2 INTRAGENIC
10q23.1(84137861_84181161)x1 pat 43.3 kb VOUS NRG3 NRG3 INTRAGENIC
16q24.3(89428111_89453232)x3 pat 25.12 kb VOUS ANKRD11 ANKRD11 1 INTRAGENIC
5q11.2(51915987_53470988)x1 mat 1.56 Mb VOUS PELO DELETED
ITGA1 DELETED
ITGA2 DELETED
MOCS2 DELETED
FST DELETED
NDUFS4 DELETED
ARL15 DELETED
6q27(165421392_165801341)x3 pat 335.6 kb VOUS PDE10A PDE10A INT END
1p32.1(59947236_60012581)x1 mat 65.35 kb VOUS FGGY FGGY INTRAGENIC
6p21.32(32179815_32312148)x1 mat 132.33 kb VOUS NOTCH4 NOTCH4 DELETED
11q14.1(84455989_84607402)x1 mat 151.4 kb LP DLG2 DLG2 2 INTRAGENIC
15q11.2(25226260_25241828)x3 mat 15.57 kb VOUS SNURF SNURF INTRAGENIC
SNHG14 INTRAGENIC
16p13.3(7041435_7132676)x1 pat 91.24 kb LP RBFOX1 RBFOX1 2 INTRAGENIC
Xp22.33(1189595_1383266)x2 Yp11.32(1162459_1322464)x2 ? 192.42 kb VOUS CRLF2 CRLF2 DUPLICATED
7q36.3(158801633_158903310)x3 mat 101.68 kb VOUS VIPR2 VIPR2 INT END
Xp22.31(7532513_8115193)x2 mat 582.68 kb VOUS VCX DUPLICATED
PNPLA4 DUPLICATED
Xp22.33(169791_537202)x2 mat 367.41 kb VOUS PLCXD1 DUPLICATED
GTPBP6 DUPLICATED
PPP2R3B DUPLICATED
3q29(196418238_196487740)x3 pat 69.5 kb VOUS PIGX INT START
PAK2 PAK2 2 INT END
13q14.11(43558077_43731680)x3 mat 173.6 kb VOUS EPSTI1 INT START
DNAJC15 DUPLICATED
2q23.1(148805626_148936476)x1 mat 130.85 kb LP MBD5 MBD5 1 INTRAGENIC
13q12.11(20413829_20445336)x3 mat 31.51 kb VOUS ZMYM5 ZMYM5 INT START
Yp11.32(771993_1322464)x2 pat 550 kb VOUS CRLF2 CRLF2 DUPLICATED
8q24.3(144825929_144881529)x3 pat 55.6 kb VOUS SCRIB SCRIB INT END
14q31.1(79388339_79657573)x1 de novo 269.24 kb P NRXN3 NRXN3 1 INTRAGENIC
13q32.2(99177988_99271292)x3 pat 93.31 kb VOUS STK24 STK24 INT START
4q25(110390080_110653618)x3 mat 263.54 kb VOUS SEC24B SEC24B INT START
CASP6 DUPLICATED
PLA2G12A DUPLICATED
4q25(113167151_113610549)x3 mat 443.4 kb VOUS AP1AR AP1AR INT START
TIFA DUPLICATED
ALPK1 DUPLICATED
NEUROG2 NEUROG2 DUPLICATED
1q21.1q21.2(145804790_147860611)x3 pat 2.06 Mb LP GPR89A INT START
NBPF11 DUPLICATED
HYDIN2 HYDIN2 2 DUPLICATED
NBPF12 DUPLICATED
PRKAB2 DUPLICATED
FMO5 DUPLICATED
BCL9 DUPLICATED
CHD1L DUPLICATED
ACP6 DUPLICATED
GJA5 DUPLICATED
GJA8 DUPLICATED
GPR89B DUPLICATED
12q24.12q24.13(112184121_112302954)x3 pat 118.83 kb VOUS ACAD10 INT START
ALDH2 DUPLICATED
MAPKAPK5 INT END
Xq12(65768203_65926180)x2 mat 155.7 kb VOUS EDA2R EDA2R DUPLICATED

A total of 46 CNVs were identified in 35 out of 122 patients (28.68%). No differences in ratios between males and females were observed: 28.9% of males (30 out of 104) and 27.8% of females (5 out of 18) tested positive for array-CGH. Among the CNVs, 16 deletions (34.8%) and 30 duplications (65.2%) were found. A total of 11 CNVs (8 deletions and 3 duplications) were intragenic (24%). When considering pathogenic and likely pathogenic CNVs, deletions were more frequent, with 9 deletions and 3 duplications. In the VOUS CNVs subgroup, 7 deletions and 27 duplications were identified, totaling 34 CNVs. One de novo CNV was found in cytoband 14q31.1 in patient A120 (0.82% of patients). The 14q31.1 microdeletion, classified as pathogenic, resulted in an intragenic deletion in the NRXN3 gene (MIM *600567). Diseases associated with NRXN3 mutations include ASD. NRXN3 is involved in neuronal cell adhesion, axon guidance, learning, and social behavior. This CNV may be considered a candidate variant for Essential ASD. Annunziata et al. [11] found 3.1% of patients with pathogenic CNVs in an Essential Autism cohort, while Pinto et al. [26] found pathogenic rearrangements in 2.8% of non-syndromic autistic patients. Noticeably, the frequency of pathogenic CNVs in essential ASD patients is significantly lower than in complex ASD patients (estimated around 10%) [6].

In this study, 11 likely pathogenic CNVs were found in 11 patients (9% of the total). Ten CNVs were inherited from a healthy parent (six maternal, four paternal); one CNV had a de novo origin. The CNVs were ranked by chromosome: 1q21.1q21.2 paternal deletion in patient A050, 1q21.1q21.2 paternal duplication in patients A054 and A124, 2q23.1 maternal deletion in patient A110, 7q11.22 maternal deletion in patient A013, 9q33.1 maternal deletion in patient A065, 11q14.1 maternal deletion in patient A080, 16p13.11 de novo deletion in patient A016, 16q21 maternal deletion in patient A017, 16p13.3 paternal deletion in patient A082, and Xp22.33 maternal duplication in patient A022.

A total of 34 CNVs were classified as VOUS in 27 ASD patients (22%). The co-occurrence of a likely pathogenic CNV and a VOUS CNV was observed in four patients (4% of the cohort). Pathogenic and likely pathogenic CNVs in 12 out of 133 essential ASD patients (9%) were previously reported by Napoli et al. [2]. Discovering P and LP CNVs in 12 patients out of 122, the results are overlapping (9.8% in our cohort). A 1q21.1q21.2 microdeletion in one patient suggests a predisposing factor for Essential Autism. The 1q21.1q21.2 reciprocal microduplication was found in two patients. This duplication is the unique recurrent CNV classified as LP in the cohort. Overlapping genes include PRKAB2, FMO5, BCL9, CHD1L, ACP6, GJA5, GJA8, and GPR89B. The 1q21.1q21.2 microduplication and reciprocal microdeletion show the same phenotype as reported in the literature. The prevalence in developmental delay and intellectual disability patients is 0.12%, compared to 0.2% for the reciprocal microdeletion. Reduced penetrance and variable expressivity were reported [27]. The intragenic microdeletion in the MBD5 gene (2q23.1) found in patient A110 could be considered a susceptibility factor for essential ASD. Deletions in this gene were reported in 0.18% of cases as responsible for autism and other neurodevelopmental diseases [28]. About 90% of individuals with MBD5 haploinsufficiency show a de novo 2q23.1 microdeletion. Additionally, partial and complete MBD5 microdeletions were inherited from a mildly affected parent [29, 30]. MBD5 is involved in nervous system development, regulation of behavior, and regulation of multicellular organism growth. The 2q23.1 microdeletion in the cohort is inherited from an apparently healthy mother, supporting incomplete penetrance.

The 7q11.22 deletion (patient A013) is an intragenic deletion in AUTS2, reported in the SFARI database (SFARI score = 1). This gene is known to be expressed in the brain and involved in neurodevelopmental disorders including ASD. AUTS2 plays a role in axon and dendrite extension, neuron migration, and actin cytoskeleton reorganization. Most pathogenic variants reported to date are de novo intragenic deletions [31], but inherited AUTS2 rearrangements are also reported [32]. In the analyzed patient, the same AUTS2 deletion is present in the healthy mother and grandmother. The 9q33.1 microdeletion (patient A065) causes the deletion of the TRIM32 gene and the intragenic deletion of ASTN2. Disruptions or deletions of TRIM32 are more frequent in male patients with Neurodevelopmental Disease (most common diagnoses: Autism, ADHD, speech-language delay). TRIM32 is highly expressed in the brain during early prenatal development, particularly in the cerebellar cortex [33]. It is involved in neurogenesis and neuron differentiation. Deletions or disruptions of ASTN2 are significantly enriched in male subjects with neurodevelopmental defects, with known reduced penetrance. ASTN2 is involved in neuron cell-cell adhesion and migration. A microdeletion in 11q14.1 found in patient A080 interrupted the DLG2 gene, reported in the SFARI database. DLG2 is involved in axonal protein transport, chemical synaptic transmission, receptor localization to synapse, and synaptic stability at cholinergic synapses. DLG2 deficiency induces autism-related behavioral phenotypes [3436]. A de novo 16p13.11 microdeletion in patient A016 predisposes to cognitive impairment, autism, seizures, and microcephaly. This variant shows variable expression and incomplete penetrance [37, 38].

The CDH8 gene was completely deleted in the 16q21 microdeletion (patient A017). CDH8 haploinsufficiency is an autism and intellectual disability susceptibility factor, playing a key role in cerebellar development. Pathogenic variants in CDH8 cause overgrowth diseases [39, 40]. A 16p13.3 microdeletion in patient A082 involved the RBFOX1 gene, reported in the SFARI database. RBFOX1 haploinsufficiency causes neurodevelopmental phenotypes including autism, intellectual disability, and epilepsy. Inherited RBFOX1 variants from healthy parents raise doubts about RBFOX1 CNVs pathogenicity [4143]. An Xq21.1 duplication found in patient A045 is a novel finding in ASD patients, with no prior reports concerning autism. The CNV is maternally inherited, suggesting possible hemizygosity effects. The recurrent CNVs found (see Supplementary Table 2, Genome build GRCh37/hg19) differ from those reported by Annunziata et al. [11]: 2p16.3 microdeletion in two patients and 15q11.2 microduplication in two patients. The recurrent CNVs in this cohort were the 1q21.1q21.2 microduplication and two microduplications, 13q12.11 (patients A006 and A113) and Yp11.32 (patients A088 and A119), which are not reported in the literature as associated with ASD. Despite their recurrence, the genes in these rearrangements do not appear central to ASD pathogenesis.

Conclusions

Our study’s comprehensive genetic analysis revealed a high prevalence of genetic variants detected through WES and array-CGH. We identified a significant number of pathogenic and likely pathogenic variants, emphasizing the importance of thorough genetic testing in understanding the etiology of autism spectrum disorders. The overall detection rate for pathogenic variants was comparable to or slightly lower than previously reported rates in the literature, while the inclusion of LP variants significantly increased the DR, suggesting their potential clinical relevance.

Pathogenic and LP variants

Our findings highlighted several recurrent genes and variants, suggesting potential new susceptibility factors for ASD. Variants in genes such as MAGEE2, AGBL4, and EPPK1, among others, were recurrent and involved in biological processes critical for neuron differentiation, axonal transport, and cytoskeletal organization.

Copy number variants (CNVs)

We detected CNVs in a significant portion of our cohort, including both deletions and duplications. Pathogenic and LP CNVs were identified in several genomic regions containing genes implicated in neurodevelopmental and synaptic functions. VOUS CNVs also revealed potentially significant genetic alterations requiring further investigation.

Clinical implications

The study’s results underscore the utility of combining WES and array-CGH in detecting genetic variants associated with ASD. The high number of variants of uncertain significance (VOUS) suggests the need for functional studies to elucidate their roles. Furthermore, the identification of recurrent variants and genes provides insights into potential genetic mechanisms underlying ASD, contributing to the growing body of knowledge necessary for improved diagnostic and therapeutic strategies. As a limitation, non-coding variants and regulation of genes were not considered, even though non-coding regions could account for a significant percentage of the ASD genetic diagnosis [44].

Future directions

Future research should focus on expanding cohort sizes and conducting functional studies to validate the clinical relevance of identified variants. Larger cohorts will help confirm new susceptibility genes and improve our understanding of ASD’s genetic architecture, ultimately aiding in the development of more targeted and effective interventions for affected individuals. Moreover, the landscape of DNA sequencing is continuously advancing, with new players and techniques to decode genetic information emerging, including the entire Genome Sequencing with short and long reads, which will provide a marginal, but important, increase in diagnostic yield for ASD patients.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 2 (558.2KB, pdf)

Acknowledgements

We thank “La Gemma Rara ODV” for the scientific support.

Author contributions

Conceptualization: PG, AZ, MFa, and RC. Data curation: PG, AZ, DC, AN, MFa and RC. Formal analysis: AZ and MFa. Funding acquisition: PG and RC. Investigation: PG, AZ, DC, and CP. Methodology: PG, AZ, MFe, PP, CL, CT, MFa and RC. Project administration: PG and RC. Resources: MFe and RC. Softwares: PG, AZ, TM and DC. Supervision: AN, DC, MFa and RC. Visualization: AZ and MFa. Writing original draft: PG, AZ, MFa and RC. Writing—review & editing: AN, MFa, and RC.

Funding

We thank Fondazione “Il Ponte del Sorriso” for the contribution.

Data availability

All data are available on European Variation Archive: https://www.ebi.ac.uk/eva/?Study-Browser&browserType=sgv. Project: PRJEB81859. Analyses: ERZ24903986.

Declarations

Ethics approval and consent to participate

The project was approved by the Ethics Committee of “ASST dei Sette Laghi” hospital in Varese, Italy on 19/12/2017.

Informed written consent was obtained from each patient. As regards the participation of children in the research, consent and authorization were signed by the parents in accordance with the rules laid down by the Ethics Committee of “ASST dei Sette Laghi” hospital.

Consent for publication

Written informed consent for publication was provided by the parents, for each patient.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

  • 1.Fernandez BA, Scherer SW. Syndromic autism spectrum disorders: moving from a clinically defined to a molecularly defined approach. Dialogues Clin Neurosci. 2017;19(4):353–71. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Napoli E, Russo S, Casula L, Alesi V, Amendola FA, Angioni A, et al. Array-CGH analysis in a cohort of Phenotypically Well-Characterized individuals with essential Autism Spectrum disorders. J Autism Dev Disord. 2018;48(2):442–9. [DOI] [PubMed] [Google Scholar]
  • 3.Mukherjee SB, Neelam, Kapoor S, Sharma S. Identification of essential, equivocal and complex autism by the Autism Dysmorphology measure: an observational study. J Autism Dev Disord. 2021;51(5):1550–61. [DOI] [PubMed] [Google Scholar]
  • 4.Ingram DG, Takahashi TN, Miles JH. Defining autism subgroups: a taxometric solution. J Autism Dev Disord. 2008;38(5):950–60. [DOI] [PubMed] [Google Scholar]
  • 5.Devlin B, Scherer SW. Genetic architecture in autism spectrum disorder. Curr Opin Genet Dev. 2012;22(3):229–37. [DOI] [PubMed] [Google Scholar]
  • 6.Drakulic D, Djurovic S, Syed YA, Trattaro S, Caporale N, Falk A, et al. Copy number variants (CNVs): a powerful tool for iPSC-based modelling of ASD. Mol Autism. 2020;11(1):42. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Bremer A, Giacobini M, Eriksson M, Gustavsson P, Nordin V, Fernell E, et al. Copy number variation characteristics in subpopulations of patients with autism spectrum disorders. Am J Med Genet B Neuropsychiatr Genet. 2011;156(2):115–24. [DOI] [PubMed] [Google Scholar]
  • 8.Glessner JT, Wang K, Cai G, Korvatska O, Kim CE, Wood S, et al. Autism genome-wide copy number variation reveals ubiquitin and neuronal genes. Nature. 2009;459(7246):569–73. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Ishizuka K, Tabata H, Ito H, Kushima I, Noda M, Yoshimi A, et al. Possible involvement of a cell adhesion molecule, Migfilin, in brain development and pathogenesis of autism spectrum disorders. J Neurosci Res. 2018;96(5):789–802. [DOI] [PubMed] [Google Scholar]
  • 10.Banerjee-Basu S, Packer A. SFARI Gene: an evolving database for the autism research community. Dis Model Mech. 2010;3(3–4):133–5. [DOI] [PubMed] [Google Scholar]
  • 11.Annunziata S, Bulgheroni S, D’Arrigo S, Esposito S, Taddei M, Saletti V, et al. CGH findings in children with complex and essential autistic spectrum disorder. J Autism Dev Disord. 2023;53(2):615–23. [DOI] [PubMed] [Google Scholar]
  • 12.Werling AM, Grünblatt E, Oneda B, Bobrowski E, Gundelfinger R, Taurines R, et al. High-resolution chromosomal microarray analysis for copy-number variations in high-functioning autism reveals large aberration typical for intellectual disability. J Neural Transm. 2020;127(1):81–94. [DOI] [PubMed] [Google Scholar]
  • 13.Ohashi K, Fukuhara S, Miyachi T, Asai T, Imaeda M, Goto M, et al. Comprehensive Genetic Analysis of non-syndromic autism spectrum disorder in clinical settings. J Autism Dev Disord. 2021;51(12):4655–62. [DOI] [PubMed] [Google Scholar]
  • 14.Sener EF, Canatan H, Ozkul Y. Recent advances in Autism Spectrum disorders: applications of whole exome sequencing technology. Psychiatry Investig. 2016;13(3):255–64. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Genovese A, Butler MG. Clinical Assessment, Genetics, and treatment approaches in Autism Spectrum disorder (ASD). Int J Mol Sci. 2020;21(13):4726. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Tammimies K, Marshall CR, Walker S, Kaur G, Thiruvahindrapuram B, Lionel AC, et al. Molecular Diagnostic Yield of Chromosomal Microarray Analysis and whole-exome sequencing in Children with Autism Spectrum Disorder. JAMA. 2015;314(9):895–903. [DOI] [PubMed] [Google Scholar]
  • 17.Francis DI, Stark Z, Scheffer IE, Tan TY, Murali K, Gallacher L, et al. Comparing saliva and blood for the detection of mosaic genomic abnormalities that cause syndromic intellectual disability. Eur J Hum Genet. 2023;31(5):521–5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Wright DC, Baluyot ML, Carmichael J, Darmanian A, Jose N, Ngo C, et al. Saliva DNA: an alternative biospecimen for single nucleotide polymorphism chromosomal microarray analysis in autism. Am J Med Genet A. 2023;191(12):2913–20. [DOI] [PubMed] [Google Scholar]
  • 19.Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med. 2015;17(5):405–23. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Viggiano M, Ceroni F, Visconti P, Posar A, Scaduto MC, Sandoni L, et al. Genomic analysis of 116 autism families strengthens known risk genes and highlights promising candidates. Npj Genomic Med. 2024;9(1):1–15. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Goh S, Thiyagarajan L, Dudding-Byth T, Mark P. Kirk. EP. A systematic review and pooled analysis of penetrance estimates of copy number variants associated with neurodevelopment. Genet Med. 2024;101227. [DOI] [PubMed]
  • 22.Riggs ER, Andersen EF, Cherry AM, Kantarci S, Kearney H, Patel A, et al. Technical standards for the interpretation and reporting of constitutional copy-number variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics (ACMG) and the Clinical Genome Resource (ClinGen). Genet Med. 2020;22(2):245–57. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Kearney HM, Thorland EC, Brown KK, Quintero-Rivera F, South ST. American College of Medical Genetics standards and guidelines for interpretation and reporting of postnatal constitutional copy number variants. Genet Med. 2011;13(7):680–5. [DOI] [PubMed] [Google Scholar]
  • 24.Stelzer G, Rosen N, Plaschkes I, Zimmerman S, Twik M, Fishilevich S, et al. The GeneCards suite: from Gene Data Mining to Disease Genome sequence analyses. Curr Protoc Bioinforma. 2016;54(1):1301–13033. [DOI] [PubMed] [Google Scholar]
  • 25.Chan AJS, Engchuan W, Reuter MS, Wang Z, Thiruvahindrapuram B, Trost B, et al. Genome-wide rare variant score associates with morphological subtypes of autism spectrum disorder. Nat Commun. 2022;13(1):6463. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Pinto D, Pagnamenta AT, Klei L, Anney R, Merico D, Regan R, et al. Functional impact of global rare copy number variation in autism spectrum disorders. Nature. 2010;466(7304):368–72. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Wang HD, Liu L, Wu D, Li T, Cui CY, Zhang LZ, et al. Clinical and molecular cytogenetic analyses of four families with 1q21.1 microdeletion or microduplication. J Gene Med. 2017;19(4):e2948. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Mullegama SV, Rosenfeld JA, Orellana C, van Bon BWM, Halbach S, Repnikova EA, et al. Reciprocal deletion and duplication at 2q23.1 indicates a role for MBD5 in autism spectrum disorder. Eur J Hum Genet. 2014;22(1):57–63. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Hodge JC, Mitchell E, Pillalamarri V, Toler TL, Bartel F, Kearney HM, et al. Disruption of MBD5 contributes to a spectrum of psychopathology and neurodevelopmental abnormalities. Mol Psychiatry. 2014;19(3):368–79. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Talkowski ME, Rosenfeld JA, Blumenthal I, Pillalamarri V, Chiang C, Heilbut A, et al. Sequencing chromosomal abnormalities reveals neurodevelopmental loci that Confer Risk across Diagnostic boundaries. Cell. 2012;149(3):525–37. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Beunders G, Voorhoeve E, Golzio C, Pardo LM, Rosenfeld JA, Talkowski ME, et al. Exonic deletions in AUTS2 cause a syndromic form of intellectual disability and suggest a critical role for the C terminus. Am J Hum Genet. 2013;92(2):210–20. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Sanchez-Jimeno C, Blanco-Kelly F, López-Grondona F, Losada-Del Pozo R, Moreno B, Rodrigo-Moreno M, et al. Attention deficit hyperactivity and Autism Spectrum disorders as the core symptoms of AUTS2 syndrome: description of five New patients and Update of the frequency of manifestations and genotype-phenotype correlation. Genes. 2021;12(9):1360. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Lionel AC, Tammimies K, Vaags AK, Rosenfeld JA, Ahn JW, Merico D, et al. Disruption of the ASTN2/TRIM32 locus at 9q33.1 is a risk factor in males for autism spectrum disorders, ADHD and other neurodevelopmental phenotypes. Hum Mol Genet. 2014;23(10):2752–68. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Yoo T, Kim SG, Yang SH, Kim H, Kim E, Kim SY. A DLG2 deficiency in mice leads to reduced sociability and increased repetitive behavior accompanied by aberrant synaptic transmission in the dorsal striatum. Mol Autism. 2020;11(1):19. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Bertini V, Milone R, Cristofani P, Cambi F, Bosetti C, Barbieri F, et al. Enhancing DLG2 implications in Neuropsychiatric disorders: analysis of a cohort of eight patients with 11q14.1 imbalances. Genes. 2022;13(5):859. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Pass R, Haan N, Humby T, Wilkinson LS, Hall J, Thomas KL. Selective behavioural impairments in mice heterozygous for the cross disorder psychiatric risk gene DLG2. Genes Brain Behav. 2022;21(4):e12799. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Nagamani SCS, Erez A, Bader P, Lalani SR, Scott DA, Scaglia F, et al. Phenotypic manifestations of copy number variation in chromosome 16p13.11. Eur J Hum Genet. 2011;19(3):280–6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Tropeano M, Andrieux J, Collier DA. Clinical utility gene card for: 16p13.11 microdeletion syndrome. Eur J Hum Genet. 2014;22(5):713–713. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Hurley S, Mohan C, Suetterlin P, Ellingford R, Riegman KLH, Ellegood J, et al. Distinct, dosage-sensitive requirements for the autism-associated factor CHD8 during cortical development. Mol Autism. 2021;12(1):16. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Ostrowski PJ, Zachariou A, Loveday C, Beleza-Meireles A, Bertoli M, Dean J, et al. The CHD8 overgrowth syndrome: a detailed evaluation of an emerging overgrowth phenotype in 27 patients. Am J Med Genet C Semin Med Genet. 2019;181(4):557–64. [DOI] [PubMed] [Google Scholar]
  • 41.Bill BR, Lowe JK, DyBuncio CT, Fogel BL. Chapter Eight - Orchestration of Neurodevelopmental Programs by RBFOX1: Implications for Autism Spectrum Disorder. In: Konopka G, editor. International Review of Neurobiology [Internet]. Academic Press; 2013 [cited 2024 Jun 24]. pp. 251–67. (Neurobiology of Autism; vol. 113). https://www.sciencedirect.com/science/article/pii/B9780124187009000083 [DOI] [PMC free article] [PubMed]
  • 42.Fernàndez-Castillo N, Gan G, van Donkelaar MMJ, Vaht M, Weber H, Retz W, et al. RBFOX1, encoding a splicing regulator, is a candidate gene for aggressive behavior. Eur Neuropsychopharmacol. 2020;30:44–55. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.O’Leary A, Fernàndez-Castillo N, Gan G, Yang Y, Yotova AY, Kranz TM, et al. Behavioural and functional evidence revealing the role of RBFOX1 variation in multiple psychiatric disorders and traits. Mol Psychiatry. 2022;27(11):4464–73. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Dominguez-Alonso S, Carracedo A, Rodriguez-Fontenla C. The non-coding genome in Autism Spectrum disorders. Eur J Med Genet. 2023;66(6):104752. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Material 2 (558.2KB, pdf)

Data Availability Statement

All data are available on European Variation Archive: https://www.ebi.ac.uk/eva/?Study-Browser&browserType=sgv. Project: PRJEB81859. Analyses: ERZ24903986.


Articles from BMC Genomics are provided here courtesy of BMC

RESOURCES