Abstract
E3 ubiquitin protein ligase encoded by ARIH2 gene catalyses the ubiquitination of target proteins and plays a crucial role in posttranslational modifications across various cellular processes. As prior documented, mutations in genes involved in the ubiquitination process are often associated with autism spectrum disorder (ASD) and/or intellectual disability (ID). In the current study, a de novo heterozygous mutation was identified in the splicing intronic region adjacent to the last exon of the ARIH2 gene using whole exome sequencing (WES). We hypothesize that this mutation, found in an ASD/ID patient, disrupts the protein Ariadne domain which is involved in the autoinhibition of ARIH2 enzyme. Predictive analyses elucidated the implications of the novel mutation in the splicing process and confirmed its autosomal dominant inheritance model. Nevertheless, we cannot exclude the possibility that other genetic factors, undetectable by WES, such as mutations in non-coding regions and polygenic risk in inter-allelic complementation, may contribute to the patient's phenotype. This work aims to suggest potential relationship between the detected mutation in ARIH2 gene and both ASD and ID, even though functional studies combined with new sequencing approaches will be necessary to validate this hypothesis.
Similar content being viewed by others
Introduction
Genomic variants located outside of the canonical splicing sites (± 2) can lead to abnormal mRNA splicing and are classified as non-canonical splicing variants (NCSVs). The clinical implications of NCSVs in neurodevelopmental disorders (NDDs) remain largely unexplored. Recent studies have underscored the role of intronic variants in disrupting critical neurodevelopmental pathways, suggesting their potential involvement in conditions such as autism spectrum disorder (ASD) and intellectual disability (ID)1,2,3. Among the potentially affected pathways, those regulated by ubiquitination enzymatic activity may be linked to the onset of neurodevelopmental disorders4. However, it is important to note that the genetic mechanisms linking non-coding DNA regions to ubiquitination and their impact on neurodevelopmental disorders remain unknown. Detecting smaller, often multiple copy number variants (CNVs) affecting putative regulatory elements may provide insights into additional risks associated with simplex neurodevelopmental disorders, including autism5,6.
Protein ubiquitination is a posttranslational modification encompassing various fundamental cellular processes7. Currently, about 600–700 ubiquitin ligase genes have been detected, representing ~ 5% of the human genes. Protein ubiquitination involves a sophisticated enzymatic cascade comprising ubiquitin-activating (E1), ubiquitin-conjugating (E2), and ubiquitin ligase (E3) enzymes8. E1 enzymes initiate the ubiquitination process by activating ubiquitin through ATP-dependent adenylation. The activated ubiquitin is subsequently transferred to a E2 enzyme, which acts as an intermediary delivering the ubiquitin to a E3 ligase9. This highly coordinated process ensures the precise attachment of ubiquitin molecules to target proteins, orchestrating a diverse array of cellular responses and functions10,11. E2-E3 complexes play a pivotal role in this process, orchestrating the attachment of ubiquitin chains to proteins. The fate of ubiquitinated proteins is determined by the type of ubiquitin chain formed. This intricate regulatory system highlights the multifaceted impact of protein ubiquitination on cellular function.
The ubiquitin–proteasome system (UPS) regulates cellular protein levels crucial for neuronal growth and function, impacting key processes in the nervous system12. Mutations in E3 ligase genes are associated with various neurological conditions13. In fact, ubiquitination is intricately linked to autism spectrum disorder (ASD), neurodevelopmental impairments, and intellectual disability (ID)9. Understanding the UPS's role in these disorders provides insights into their molecular mechanisms, influencing neural development and signalling pathways like WNT, mTOR, and TGFβ. UPS activity directly influences axonal and dendritic development, synaptic maturation, and pruning14,15,16. E3 ligase genes are implicated in ASD, schizophrenia, ID, epilepsy, Parkinson’s disease, and Angelman syndrome, highlighting their broad impact on neurological health9,13,17,18,19,20.
E3 enzymes are categorized into three distinct groups: the really interesting new gene (RING) group, the homologous to E6-AP carboxyl terminus (HECT), and the RING-between-RING (RBR) E3 family. RING ligases operate by directly transferring ubiquitin from E2 enzymes to the substrate through substrate hydrolysis. In contrast, HECT and RBR E3 ligases follow a distinct mechanism. They catalyse ubiquitin transfer to a lysine residue on the E3 ligase itself before subsequently transferring it to the target substrate9. Within this context, Ariadne RBR E3 ubiquitin protein ligase 2 (ARIH2) is a RBR family member, which exhibits unique E3 ligase activity, interacting with Ubiquitin-conjugating enzyme E2 L3 (UBE2L3) and functioning similarly to HECT-type E3 enzymes. Particularly, ARIH2 catalyzes ubiquitination of target proteins together with UBE2L321,22. These enzymes bind E2s through the first RING-type zinc finger, requiring an obligate trans-thiolation step for ubiquitin transfer involving a conserved cysteine residue in the second RING-type zinc finger23.
The E3 ubiquitin protein ligase enzyme encoded by ARIH2 gene comprises 8 highly conserved domains, encompassing three zinc finger type domains: RING-type 1, IBR-type and RING-type 224. As previously documented, E3 ubiquitin protein ligase is autoinhibited by the Ariadne domain, which masks the active site within the second RING-type zinc finger domain, thereby inhibiting E3 activity19. Within this context, ARIH2 ubiquitinates substrates of E3 ubiquitin ligase complexes composed of the neddylated forms of Cullin 5 and RING-box protein 2 (neddylated CUL5-RBX2 E3s). Structural analyses reveal ARIH2's distinctive autoinhibition and activation upon association with neddylated CUL5-RBX2, interacting with CUL5 and NEDD825,26.
ARIH2 gene is intricately involved in embryonic development through its direct interaction with Hedgehog signalling and myelopoiesis process27,28. In particular, it directly interplays with Hedgehog signalling through smoothened ubiquitylation and endoplasmic reticulum—associated degradation28. According to documented evidence, ARIH2 gene is ubiquitously expressed, showing its highest expression levels in granulocytes29. Additionally, ARIH2 shows high expression patterns in several brain tissues, including amygdala, basal ganglion, cerebellar hemispheres, cerebellar vermis, and cerebral cortex (The Human Protein Atlas). Disorders in these brain regions were previously described as potentially involved to neurodevelopmental diseases including ASD and ID30,31,32. ARIH2 is a paralog of ARIH1 gene, and both participate in DNA repair against genotoxic stress and potentially mediate mRNA translation arrest due to its shared Ariadne domain33. The human homolog of Ariadne and counterparts in Drosophila and Caenorhabditis elegans are implicated in regulating translation, cellular proliferation, and developmental processes34,35.
The objective of this study was to verify a new potential relationship between ASD and ID and a de novo novel mutation in an intronic splicing region adjacent to the last exon of ARIH2 gene. This report contributes to further reinforce the knowledge of the genetic basis related to ASD and ID, suggesting the possible involvement of the Ubiquitin E3 ligase pathway in the manifestation of these neurodevelopmental disorders. Additionally, it raises the possibility that mutations in intronic regions, which are often undetectable by WES, may significantly contribute to the patient's phenotype.
Results
Clinical report
The 20-year-old girl was the second daughter of healthy, non-consanguineous parents. She was born at term; no complications occurred during pregnancy. The birth weight registered was 3100 g (z-score: − 0.3), the length was 52 cm (z-score: 1.5) At birth, she presented jaundice, that did not require phototherapy. She presented psychomotor delay: autonomous walking occurred at 20 months of age, first words at 18–20 months of age, sphincter control at the age of 5. When she was 2 years old, the first relational abnormalities were noted: she tended to hide behind her mother, when called, she didn’t promptly answer. At the kindergarten, at the age of 3, she was very shy, spoke softly, she used to play putting the dolls one behind the other, sometimes she launched them. Subsequently, she started to manifest behavioral problems: anxiety reactions, mood instability, repetitiveness, a strong addiction for the mum, episodes of loss of control, hand stereotypies, nocturnal hyperphagia. She was diagnosed of ASD at the age of 10 and treated with quetiapine, risperidone, lamotrigine, cariprazine, without benefit. Brain MRI was unremarkable.
In the 7 months preceding the admission to our department, at the age of 19, she presented frequent episodes (more times per week), of feeling of anxiety, cough, vomiting, headache, lasting for many hours. A slowing in movements and a delay before starting to speak were also noted at that time.
At the age of 20, the clinical phenotype was characterized by downwards-pointing eyelid fissures, posterior auricles, kyphoscoliosis, hand-stereotypies, accentuated during speech, bilateral postural tremor and tendency to keep the hands flexed during walking. Her weight was 54 kg (25–50 centile), her height was 151.5 cm (3–10 centile), her BMI was 23.68 kg/m2, head circumference was 55 cm (50–75 centile). At that time, she was treated with haloperidol 2 mg/die, melatonin 2 mg/die. In order to manage her behavioral symptoms, olanzapine was added to her therapy, at the dosage of 10 mg/die, with improvement. The EEG showed sharp-waves and spikes over the temporal regions of the left hemisphere, with tendency to contralateral propagation. Furthermore, magnetic resonance imaging (MRI) of the brain displayed normal results. From a psychological point of view, the diagnosis of ASD level 2 was confirmed, and a diagnosis of moderate ID was made. Comparative genome hybridization (CGH) array didn’t reveal any CNV alterations.
Genetic analysis by next generation sequencing
Whole exome sequencing revealed the presence of a heterozygous de novo nucleotide variation at position c.1411-3C > T, within the last intron in the ARIH2 gene (NM_006321) (Fig. 1).
(a) Graphical representation of the heterozygous de novo variation identified within ARIH2 gene. Images display data from the patient (Pt), the mother (Mo), and the father (Fa). The novel mutation, detected using the Integrative Genome Viewer (IGV) system, is illustrated. At the bottom is displayed the nucleotide sequence and the corresponding amino acids of the region. (b) The de novo mutation was confirmed through conventional Sanger sequencing in the patient (Pt), the mother (Mo), and the father (Fa).
Sanger sequencing on the parents confirmed the presence of this mutation only in the patient affected by ASD (Fig. 1). WES analysis unveiled no additional mutations directly or potentially associated with other known ASD and/or ID related genes. Furthermore, to confirm that the observed mutation can be considered a de novo mutation, short tandem repeat (STR) polymorphisms were analysed in the patient/mother/father subjects, confirming their parenthood.
The mutation is situated at -3 base pairs from the terminal exon, which encodes the final segment of the Ariadne domain (amino acids 359 to 493) as depicted in Fig. 2. Conversely, the nucleotide variation observed resulted in a change, from T to C, within the splicing region of donor site sequence, adjacent to the last exon. The causative pathogenetic effect of this specific variant was obtained on the assessment conducted using the ACMG criteria and, more specifically, three criteria for the classification were used, supporting (PP4), moderate (PM2), and strong (PS2) association.
(a) Depiction of the ubiquitination mechanism. Specifically, this process involves E1, E2, and E3 enzymes. Precisely, E1 initiates the process by the ubiquitin activation (step 1). Subsequently, the activated ubiquitin is transferred to an E2 enzyme (step 2), which delivers it to an E3 ligase (step 3). This process ensures the targeted attachment of ubiquitin to a protein substrate, regulating various cellular functions. (b) Autoinhibition of the E3 ubiquitin protein ligase activity operated by the Ariadne domain. Specifically, this domain blocks the second RING-type zinc finger domain, thereby inhibiting E3 activity. Cullin-5 (CUL5) and NEDD8 (N8) are core components of the E3 ubiquitin-protein ligase complex which mediate the proteasomal degradation of target proteins26. The graphical representation is a modified version of a previous model related to ARIH1 (whose gene is paralog of ARIH2) having the same domains pattern organization: acidic residues (AC)-UBA-RING1-IBR-RING2-Ariadne36. (c) Graphical representation of the 8 highly conserved domains within the ARIH2 protein. The figure also highlights the specific position of the identified mutation (c.1411-3C > T), that likely affects the encoding region of the ARIH2 protein from amino acid 471, within the last portion of the Ariadne domain. The figure was modified from the Uniprot protein database.
In silico splicing prediction
In-silico splicing prediction analysis was performed considering the putative new donor/acceptor splicing sites identified close to the start of the exon 16 of the ARIH2 gene (Fig. 3). The analysis taken in consideration the new putative donor site “gt”, directly obtained by the variant c.1411-3C > T, further to the putative acceptor site “ag” at the position 48,983,157 (Fig. 3b,c). The putative "gt" donor site formation, in addition to the predicted constitutive acceptor "ag" (located 38 base pairs upstream of the mutation site), may introduce a new exon codifying for 11 amino acids, due to the following “TGA” Stop codon (Fig. 3c).
In silico splicing predictions related to the variant c.1411-3C > T in the ARIH2 gene. (a) Genomic sequence of the exon 15 and 16, and the intron between them, of the ARIH2 gene. Exon and intron sequences are in uppercase and lowercase letters, respectively. The red lines indicate the translated sequences. The “ag” blue light and the “gt” green nucleotides indicate the acceptor/donor splicing sites respectively. The TAA sequence in a red box indicate the stop codon. On the left, the genomic position, on the chromosome 3, of the first nucleotide on the same line, were indicated. The red “c” nucleotide indicated the site involved in the c.1411-3C > T variant. (b) Genomic sequence of the exon 16 and the last part of the intron with the c.1411-3C > T variant (red nucleotide) showing the “ag” (red circle) and the “gt” (blue circle) putative splicing sites. The blue light box indicates the acceptor splicing site determining the wild type mRNA formation. (c) Genomic sequence as in (b). The blue light box indicates the acceptor splicing site determining, if used, a different mRNA formation, which include a sequence with a stop codon (indicated by the red box) after 11 codons. Red circle indicates the “ag” splicing sites here not used. (d) Schematic representation of the two mRNA variants, and the relative amino acid codified, on the basis to the use of the two “ag” acceptor sites shown in “b”, and (c). Alt. Exon 16: alternative exon 16 present in the mRNA in the case the “ag” splicing site at position 48,983,157 is used. Exons, introns, and mRNA are not to scale.
The predictive analysis performed with DOMINO described this gene as having an autosomal dominant (AD) inheritance pattern (probability of AD: 0.6318). Furthermore, the variant was classified by FATHMM, Reg-SNP-intron and Mutation taster algorithms as disease causing (Table 1).
In-silico splicing prediction analysis conducted using ASSP and Spliceator algorithms revealed that the identified variant created a novel “gt” donor gain site, as result of the genetic variant c.1411-3C > T within ARIH2 (Fig. 3), further to the constitutive acceptor sites "ag", located 38 base pairs upstream of the mutation site. Both utilized tools categorized the variant site as a potential new alternative isoform or cryptic donor (Fig. 3 and Table 2). The newly generated donor site as a consequence of the mutation exhibits scores of 4.554 and 0.711 for ASSP and Spliceator, respectively. In addition, the prediction indicated the presence of a plausible constitutive acceptor site "ag" located 38 base pairs upstream of the mutation site exhibiting high scores (9.280 and higher than 0.7 according to ASSP and Spliceator, respectively) (Table 2). As predicted, both acceptor and donor sites may introduce a new exon consisting of 11 amino acids and a “TGA” Stop codon (Fig. 3).
In addition, the analyses conducted using NNSplice tool and Mutation Taster, revealed a candidate donor site alteration in the intronic region adjacent to the last exon of the ARIH2 gene resulting with a splice site gain score of 0.37 (Table 3). Furthermore, PhyloP score exhibited the value of 1.58, indicating a moderate grade of conservation of the analysed splicing region. Conversely, PhastCons score for the splicing region at the mutation site was 0.914 (Table 3).
Hydrogen bonds assessment
The analysis conducted using UCSF ChimeraX revealed a total of 42 hydrogen bonds within the region of the Ariadne domain, specifically corresponding to the segment affected by the mutation spanning from amino acid 471 to 493. These electrostatic bonds spanned between intra and extra Ariadne domain (359–493 aa). Notably, six of these interactions involved domains other than the Ariadne one (Fig. 4). Specifically, these bonds included interactions between the residues His491 (one hydrogen bond) and Asp492 (two hydrogen bonds) with Tyr264 and Arg245, respectively. Remarkably, both residues were situated within the zinc finger RING 1 domain. Additionally, these electrostatic interactions implicated the residues Arg483 (two hydrogen bonds) and Arg484 (one hydrogen bond), with interactions occurring between Glu57 (comprising an extra domain region) and Glu47 (UBA-like domain), respectively. STRING analysis revealed the correlation between E3 ubiquitin protein ligase and NEDD8, CUL5, RFN7 and UBE2L3 proteins. Specifically, these correlations were based on experimental evidence.
(a) Wild type and (b) mutated E3 ubiquitin protein ligase of ARIH2 gene. (c-f) Ariadne domain: graphical representation of amino acid residues involved in hydrogen bond interactions in the last portion of the Ariadne domain (from 471 to 493 aa), including the last helix of the Ariadne domain (comprising from aa 469 to aa 491). This gene was affected by a de novo mutation in the intronic region at − 3 bp from the exon 16 of ARIH2 gene. The figure illustrates six hydrogen bonds involving the region spanning from 471 to 493 aa and extra Ariadne domain residues: (c) one hydrogen bond between residues HIS491 and TYR264 (zinc finger RING 1 domain); (d) two hydrogen bonds between residues ASP492 and ARG245 (zinc finger RING 1 domain); (e) one hydrogen bond between residues ARG484 and GLU47 (UBA-like domain); (f) two hydrogen bonds between residues ARG483 and GLU57. The images were realized using the software UCSF Chimera X.
Discussion
Genetic variants outside the canonical splicing sites can disrupt normal mRNA splicing, potentially impacting neurodevelopmental disorders clinically. Furthermore, mutations in genes involved in the ubiquitination process are often associated with ASD and/or ID37,38. The UPS intricately interplays with the non-lysosomal proteolytic pathway regulating cellular protein levels. This regulatory mechanism extends to proteins crucial for neuronal growth and function, emphasizing UPS's central role in modulating key cellular processes within the nervous system12.
Here we report details on the identification of a de novo, heterozygous mutation (c.1411-3C > T) localized in the splicing region (at − 3 bp from the last exon) in ARIH2 gene, detected through next generation sequencing. This variation was detected in a patient exhibiting both ASD and ID. To date, ARIH2 doesn’t have an assigned OMIM number and code. Nevertheless, the predictive analysis performed with DOMINO identified ARIH2 gene as having an autosomal dominant (AD) inheritance pattern (probability of AD: 0.6318). The comprehensive whole exome analysis revealed no additional mutations directly or potentially associated with other known ASD and ID related genes. However, we cannot exclude the possibility that other genetic factors, undetectable by WES, may contribute to the phenotype. This specific variant has never been described in gnomAD and 1000G databases. We suggest a potential relationship between the pathogenic effect of this specific variant, based on the assessment conducted using the ACMG criteria. Additionally, the in silico analysis conducted using the Mutation Taster, FATHMM, and RegSNPs-intron tools revealed a potential pathogenic significance of the identified variant (Table 1).
Moreover, in silico splicing predictions conducted using the NNSplice, ASSP, and Spliceator algorithms revealed with high score that the identified variant (c.1411-3C > T) created a novel donor gain site, represented by the mutated "GT" sequence. In addition, the prediction analysis performed, indicated the presence of a plausible constitutive acceptor site "AG" located 38 base pairs upstream of the mutation site exhibiting high scores (Fig. 3, and Table 2). As predicted both acceptor and donor sites may introduce a new exon. This exon consists of 11 amino acids and a “TGA” stop codon.
For further support these findings, Mutation Taster yielded positive scores for both PhyloP and PhastCons, indicating a moderate and high conservation rate, respectively, at the specific site of the variant. Indeed, "GT" is a well-established sequence often associated with alternative donor sites in eukaryotic splicing39. Based on this prediction, we hypothesize that the splicing process alteration may disrupt the encoding of the last protein portion, resulting in a misfolded E3 ubiquitin protein ligase. Furthermore, it's important to note that intronic variants at position -3 in genes like NF1, TSC1, and PAH, (as indicated by HGMD database) constitute approximately 4% of causative mutations within intronic regions. This underscores the significance of exploring such variants in elucidating their potential contributions to pathogenicity, despite the limitations related to the possible presence of other variants not identified by WES analysis. We emphasize that a comprehensive understanding of the alternative splicing process would necessitate experimental studies on mRNA/cDNA, which, regrettably, are not currently possible.
Our hypothesis emphasizes that this splicing mutation alters the polypeptide chain of E3 ubiquitin protein ligase enzyme altering the last portion of the Ariadne domain (Fig. 2 and Fig. 4). The prediction of hydrogen bonds in the disrupted portion of the ARIH2 protein revealed the engagement of six significant hydrogen bonds between this region (471–493 aa) and other functional domains than Ariadne. Based on these findings, we propose that the absence of these electrostatic interactions has an impact on protein function. We underscore that the protein structure prediction conducted with UCSF ChimeraX considers elements such as the arrangement of alpha helices, beta strands, and loops. However, as limiting factor, it may not provide precise explicit modeling of metal ion binding sites like Zn2+. Nonetheless, as the prediction leverages the AlphaFold deep learning algorithm, it might indirectly capture certain metal ion interactions.
As previously documented, E3 ubiquitin protein ligase is autoinhibited by the Ariadne domain, which masks the active site within the second RING-type zinc finger domain, thereby inhibiting E3 activity36. Ariadne domain in Drosophila and Caenorhabditis elegans within ARIH1 gene (paralog of ARIH2) have been implicated in the transcriptional and translational regulation34,35. As previously reported40, these processes, in a diverse group of genes, were associated with both syndromic and non‐syndromic forms of ASD. Despite ARIH1 and ARIH2 deriving from a common ancestral gene, their protein sequences exhibit low homology (34.91% overall and 38.06% in the Ariadne domain). Nevertheless, they have the same domains pattern organization (AC-UBA-RING1-IBR-RING2-Ariadne). While limited structural information exists on the IBR domain, protein structure predictions suggest potential hydrogen bond formation between the IBR and Ariadne domains (specifically between Asp 492 and Arg 245, as well for His 491 and Tyr 264) (Fig. 4). Given the structural proximity identified between the Ariadne and IBR domains, these electrostatic interactions seem plausible based on our protein structure prediction analysis41,42,43. Building upon these hypotheses, it is likely that the disruption of the Ariadne domain significantly impacts, altering post-transcriptional modifications of the target protein, which might potentially contribute to the development of ASD and ID.
As previously documented, E3 ligases genes have been linked to neurological disorders that include neurodevelopmental or neurodegenerative diseases, such as autism, schizophrenia, intellectual disability, epilepsy, Angelman syndrome, and Parkinson’s disease9,13,17,18,19,20. As was outlined, the alteration of the E3 ubiquitin protein ligase structure in patients showing ASD, negatively interacts with synaptic function and plasticity, altering learning and memory formation by targeting activity regulated cytoskeleton-associated protein (Arc), a Rho guanine nucleotide exchange factor (Ephexin5), and small conductance calcium-activated potassium channel (SK2)37,44,45. In particular, several E3 ligases are encoded by various genes, such as UBE3A, UBE3B, TRIP12 and HUWE1 showing specific pathogenic variations associated to Autism37,38,46.
Interestingly, ARIH2 gene expression was observed in several brain tissues, including amygdala, basal ganglion, cerebellar hemispheres, cerebellar vermis and cerebral cortex, tissues potentially involved in ASD30,31,32,47. Moreover, previous studies indicated a differential expression of ARIH2 in post-mortem cerebral cortex tissue between individuals with ASD and neurotypical controls. Specifically, ARIH2 was found to be downregulated in ASD patients48,49.
ARIH2 was investigated in a cohort of patients analyzed for the detection of rare coding variations by population genetic approach, aiming to provide valuable insights into the genetic architecture and phenotypic context of autism50. Within this context, two de novo variants were detected in 5’ UTR and intronic regions of ARIH2 gene, exhibiting an uncertain correlation with autism. It’s worth mentioning that an additional de novo mutation, in the ARIH2 gene, involving a repeated motif AAG-1 was previously reported in a proband affected by ASD51. A prior study conducted a predictive analysis focused on loss-of-function mutations in six genes, considering factors such as the extent of brain expression, haploinsufficiency index, functional knowledge about gene homology, and insights from mouse models. This analysis identified ARIH2 as a candidate gene associated with ID52. Furthermore, ARIH2 was postulated to be part of a subset of intelligence-related genes, characterized by intra-species variations in human populations. These genes may also be evolution-related, exhibiting inter-species variations between humans (Homo sapiens) and great apes (including P. troglodytes and P. abelii)53.
The analysis performed with STRING based on experimental evidence of the protein pathways through the study of protein–protein interactions, revealed a significant allosteric specificity among ARIH2, CUL5 and NEDD8 genes. The latter was reported as likely associated to ASD45. Specifically, all these genes (ARIH2, NEDD8, CUL5) interplay with the conjugation and ubiquitination activities mediating the subsequent proteasomal degradation of target proteins (Fig. 2b). Notably, NEDD8 uniquely contacts covalently linked CUL5, inducing structural rearrangements that expose previously hidden regions of ARIH226. Furthermore, there is evidence supporting the role of NEDD8 and CUL5 in regulating mammalian excitatory synapses and neural development54,55.
Notably, we are hypothesizing that the splicing mutation that we detected might be associated with ASD and ID similarly to the prior studied mutations in genes encoding for E3 ubiquitin protein ligase. Additionally, it is important to emphasize a potential limitation: variants in non-coding regions, such as those associated with promoter regions, may also contribute to the ASD phenotype56. Within this context, it is essential to acknowledge that while Whole Exome Sequencing (WES) is a powerful tool for identifying coding mutations, it may not capture genetic variations in non-coding regions or complex polygenic interactions1,57. These undetected mutations, including those in non-coding regions and polygenic risks arising from inter-allelic complementation, could potentially play significant roles in shaping the patient's phenotype58. A limitation of our WES analysis is the filtering out of polymorphisms with Minor Allele Frequencies (MAF) higher than 1%, which may contribute to polygenic risk. The limitations of WES in detecting these variants underscore the need for complementary approaches, such as Whole Genome Sequencing (WGS) or targeted sequencing of specific regulatory elements, to fully elucidate the genetic landscape underlying complex neurodevelopmental disorders59,60. Integrating these techniques with advanced bioinformatic analyses will be crucial for uncovering the complete spectrum of genetic factors contributing to the phenotype.
Although several studies have identified the strong role of ubiquitination in autism and intellectual disability, the association between ARIH2 gene and these conditions that we are proposing is only a hypothesis. In fact, further patients exhibiting ASD or ID with variants in the ARIH2 gene are needed to validate our study. Further in vitro functional assays on ARIH2 gene are essential to test the validity of the novel gene and to enhance our understanding of the complex interactions among genes encoding proteins in ASD.
Understanding ubiquitination's role in cellular processes offers insight into disease mechanisms and therapeutic avenues. Drugs targeting ubiquitin enzymes can modulate protein degradation, suggesting potential therapeutic interventions61,62,63. Therefore, comprehending ubiquitination and its implications in cellular physiology and pathology can lay the basis for the development of novel therapeutic approaches for various diseases.
Conclusion
In this study, we report a patient showing both ASD and ID. Whole exome sequencing (WES) enabled the identification of a de novo heterozygous mutation in the ARIH2 gene encoding for an E3 ubiquitin protein ligase. Notably, this novel mutation is located in the intronic region adjacent to the last exon of this gene. Based on a comprehensive assessment of its plausible pathogenic role, we hypothesize a potential relationship between ARIH2 and the patient's phenotype. Nevertheless, we cannot rule out the possibility that other genetic factors, which are undetectable by WES, could determinate or contribute to the patient's phenotype. It is worth mentioning that E3 ubiquitin ligases are a large family of enzymes widely documented as implicated in ASD and ID. Our hypothesis is that the mutation alters the last portion of the Ariadne domain involved in autoinhibition of the E3 ubiquitin ligase protein modulating proteasomal degradation. ARIH2 gene lacks an assigned OMIM number. We propose for the first time an association between this gene and ASD/ID. Further functional studies are needed in autistic patients exhibiting ARIH2 variants, to validate the current study.
Materials and methods
Library preparation and NGS analysis
Genomic DNA was isolated from peripheral blood leukocytes obtained from the clinical case, as well from the father and the mother. The extraction protocol applied was a non-organic and non-enzymatic extraction method previously developed64. Exome analysis was performed using the Ion AmpliSeq™ Exome RDY kits, following the manufacturer’s instructions (Thermo Fisher Scientific, Waltham, MA, USA). The quality of libraries was assessed using DNA 1000 chips on the Tape Station 4200 (Agilent, Santa Clara, CA, USA) and Qubit dsDNA BR Assay kits (Invitrogen, Waltham, MA, USA). Template preparation, clonal amplification, recovery, and enrichment of template-positive Ion Sphere™ particles and loading of sequencing-ready Ion Torrent semiconductor chips were performed with the Ion Chef™ system (Thermo Fisher Scientific, Waltham, MA, USA). Finally, we sequenced each loaded Ion 550™ chip on the S5 system (Thermo Fisher Scientific, Waltham, MA, USA). Overall, 98% of regions of interest have a minimum coverage of at least 20 × . Data of runs were processed using the Ion Torrent Suite 5.16, Variant Caller 5.16, Coverage Analysis 5.16 (Thermo Fisher Scientific, Waltham, MA, USA), Ion Reporter (Thermo Fisher Scientific, Waltham, MA, USA), and/or wANNOVAR tools65. DNA sequences were displayed using Integrated Genomics Viewer66. The reference genome employed for the analysis was Hg38. Pathogenic variant was confirmed through conventional Sanger sequencing. The methods related to the Variant Caller parameters and PCR setup were available in the Supplementary File 1. DNA fingerprint analysis was performed for both patient and parents, according to a previous protocol67, to confirm maternity and paternity, and de novo event.
Data analysis
The observed nucleotide variation was classified according to the “American College of Medical Genetics” (ACMG) guidelines68 and it was performed with VarSome69, and the three criteria used for the classification used were reported in Table 4.
For the in silico evaluation of the pathogenic significance of the variant, we utilized the MutationTaster algorithm (https://www.mutationtaster.org/) (accessed on 15 November 2023) along with the FATHMM (https://fathmm.biocompute.org.uk/) and RegSNPs-intron (https://regsnps-intron.ccbb.iupui.edu/) tools (accessed on 17 April 2024). These tools assign output values ranging from 0 to 1, indicating the pathogenic significance of the variant70,71.
Protein sequence and domains were obtained from the free online database of UniProt (https://www.uniprot.org/) (accessed on 15 November 2023) (UniProt Consortium, 2015). Expression level was ascertained on The Human Protein Atlas (https://www.proteinatlas.org/) (accessed on 15 November 2023)72.
The in silico prediction of the splicing process was performed using NNSplice tool, provided by Mutation Taster website, in addition to ASSP (http://wangcomputing.com/assp/) and Spliceator (https://www.lbgi.fr/spliceator/) tools (accessed on 17 April 2024). ASSP scores range from 0 to 10, with higher scores indicating increased likelihood of a splice site. Cutoff values of 2.2 for acceptor sites and 4.5 for donor sites achieve correct identification rates of approximately 75% and 80%, respectively, for false and alternative isoform/cryptic splice sites73,74. Spliceator scores range from 0 to 1, with higher scores indicating higher likelihood of a sequence being recognized as a splice site75.
The confidence, PhyloP and PhastCons scores were analysed according to previous studies76,77,78. Notably, a mutation taster splice site gain score higher than 0.3 indicates gain of a completely new splice site. Conversely, PhyloP and PhastCons scores assess conservation rate in the analysed region. Within this context, PhyloP score spans between -14 and 6. Sites predicted to be conserved are assigned positive scores, while sites predicted to be fast evolving are assigned negative scores. On the other hand, PhastCons range between 0 and 1.
Additionally, in silico conservation rate was analyzed by DOMINO with the score provided by VarSome database (accessed on 15 November 2023)69, according to prior research79,80. For all the bioinformatic tools employed were used the default parameters. The Human Gene Mutation Database (HGMD) (https://www.hgmd.cf.ac.uk/) (accessed on 17 April 2024)81 was utilized to determine the percentage of intronic variants located at position -3 from various exons, which have been confirmed to have causative effects in genes such as NF1, TSC1, and PAH. STRING analysis was conducted for analyzing the protein pathways correlated with ARIH2 gene based on experimental studies (https://string-db.org/) (accessed on 15 November 2023)82.
Molecular graphics and analyses performed with UCSF ChimeraX, developed by the Resource for Biocomputing, Visualization, and Informatics at the University of California, San Francisco, with support from National Institutes of Health R01-GM129325 and the Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases83.
Institutional review board statement
All procedures performed in this study were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. This study was conducted in accordance with the Declaration of Helsinki and approved by the local Ethics Committee “Comitato Etico IRCCS Sicilia-Oasi Maria SS”. Prot. CE/88bis, as of 20 March 2019, approval code: 2019/03/18/CE-IRCCS-OASI/18.
Informed consent statement
Written informed consent has been obtained from the patient’s parents to publish this article.
Data availability
The datasets analysed during the current study are available in the ClinVar repository, acc. No. VCV002692232.1 (Variation ID: 2692232). [Web link: https://www.ncbi.nlm.nih.gov/clinvar/variation/2692232/?oq=2692232&m=NM_006321.4(ARIH2):c.1411-3C%3ET]. Figure 2C data are from Uniprot protein database. Accession: https://www.uniprot.org/uniprotkb/O95376/entry, family & domains section. Accessed on 19/02/2024.
References
An, J.-Y. et al. Genome-wide de novo risk score implicates promoter variation in autism spectrum disorder. Science https://doi.org/10.1126/science.aat6576 (2018).
Dhaene, E. & Vergult, S. Interpreting the impact of noncoding structural variation in neurodevelopmental disorders. Genetics in Medicine 23, 34–46 (2021).
Li, K. et al. Prioritizing de novo potential non-canonical splicing variants in neurodevelopmental disorders. EBioMedicine 99, 104928 (2024).
Manoubi, W. et al. Genetic investigation of the ubiquitin-protein ligase E3A gene as putative target in Angelman syndrome. World J. Clin. Cases 12, 503–516 (2024).
Turner, C. M. et al. Increased expression of the pro-apoptotic ATP-sensitive P2X7 receptor in experimental and human glomerulonephritis. Nephrol. Dial. Transplant. 22, 386–395 (2006).
Pagnamenta, A. T. et al. Structural and non-coding variants increase the diagnostic yield of clinical whole genome sequencing for rare diseases. Genome Med. 15, 94 (2023).
Schmidt, M. F., Gan, Z. Y., Komander, D. & Dewson, G. Ubiquitin signalling in neurodegeneration: mechanisms and therapeutic opportunities. Cell Death Differ. 28, 570–590 (2021).
Ullah, K., Zubia, E., Narayan, M., Yang, J. & Xu, G. Diverse roles of the E2/E3 hybrid enzyme <scp>UBE</scp> 2O in the regulation of protein ubiquitination, cellular functions, and disease onset. FEBS J. 286, 2018–2034 (2019).
Kasherman, M. A., Premarathne, S., Burne, T. H. J., Wood, S. A. & Piper, M. The Ubiquitin System: a Regulatory Hub for Intellectual Disability and Autism Spectrum Disorder. Mol. Neurobiol. 57, 2179–2193 (2020).
Martínez-Noël, G. et al. Network Analysis of UBE3A/E6AP-Associated Proteins Provides Connections to Several Distinct Cellular Processes. J. Mol. Biol. 430, 1024–1050 (2018).
Toma-Fukai, S. & Shimizu, T. Structural Diversity of Ubiquitin E3 Ligase. Molecules 26, 6682 (2021).
Crider, A., Pandya, C. D., Peter, D., Ahmed, A. O. & Pillai, A. Ubiquitin-proteasome dependent degradation of GABAAα1 in autism spectrum disorder. Mol. Autism. 5, 45 (2014).
George, A. J., Hoffiz, Y. C., Charles, A. J., Zhu, Y. & Mabb, A. M. A Comprehensive Atlas of E3 Ubiquitin Ligase Mutations in Neurological Disorders. Front. Genet. https://doi.org/10.3389/fgene.2018.00029 (2018).
Kumar, D., Ambasta, R. K. & Kumar, P. Ubiquitin biology in neurodegenerative disorders: From impairment to therapeutic strategies. Ageing Res. Rev. 61, 101078 (2020).
Zajicek, A. & Yao, W.-D. Remodeling without destruction: non-proteolytic ubiquitin chains in neural function and brain disorders. Mol. Psychiatry 26, 247–264 (2021).
Tang, G. et al. Loss of mTOR-Dependent Macroautophagy Causes Autistic-like Synaptic Pruning Deficits. Neuron 83, 1131–1143 (2014).
Upadhyay, A. et al. E3 Ubiquitin Ligases Neurobiological Mechanisms: Development to Degeneration. Front Mol. Neurosci. https://doi.org/10.3389/fnmol.2017.00151 (2017).
Ardley, H. C. & Robinson, P. A. The Role of Ubiquitin-Protein Ligases in Neurodegenerative Disease. Neurodegener. Dis. 1, 71–87 (2004).
Hampe, C., Ardila-Osorio, H., Fournier, M., Brice, A. & Corti, O. Biochemical analysis of Parkinson’s disease-causing variants of Parkin, an E3 ubiquitin–protein ligase with monoubiquitylation capacity. Hum. Mol. Genet. 15, 2059–2075 (2006).
Conway, J. A., Kinsman, G. & Kramer, E. R. The Role of NEDD4 E3 Ubiquitin-Protein Ligases in Parkinson’s Disease. Genes (Basel) 13, 513 (2022).
Buetow, L. & Huang, D. T. Structural insights into the catalysis and regulation of E3 ubiquitin ligases. Nat. Rev. Mol. Cell. Biol. 17, 626–642 (2016).
Zhang, Y. & Hou, L. Alternate Roles of Sox Transcription Factors beyond Transcription Initiation. Int. J. Mol. Sci. 22, 5949 (2021).
Scott, D. C. et al. Two Distinct Types of E3 Ligases Work in Unison to Regulate Substrate Ubiquitylation. Cell 166, 1198-1214.e24 (2016).
Kawashima, A. et al. ARIH2 Ubiquitinates NLRP3 and Negatively Regulates NLRP3 Inflammasome Activation in Macrophages. J. Immunol. 199, 3614–3622 (2017).
Lamsoul, I., Uttenweiler-Joseph, S., Moog-Lutz, C. & Lutz, P. G. Cullin 5-RING E3 ubiquitin ligases, new therapeutic targets?. Biochimie 122, 339–347 (2016).
Kostrhon, S. et al. CUL5-ARIH2 E3–E3 ubiquitin ligase structure reveals cullin-specific NEDD8 activation. Nat. Chem. Biol. 17, 1075–1083 (2021).
Lin, A. E. et al. ARIH2 is essential for embryogenesis, and its hematopoietic deficiency causes lethal activation of the immune system. Nat. Immunol. 14, 27–33 (2013).
Lv, B., Zhang, X.-O. & Pazour, G. J. Arih2 regulates Hedgehog signaling through smoothened ubiquitylation and ER-associated degradation. J. Cell Sci. https://doi.org/10.1242/jcs.260299 (2022).
Marteijn, J. A. F. et al. The E3 ubiquitin-protein ligase Triad1 inhibits clonogenic growth of primary myeloid progenitor cells. Blood 106, 4114–4123 (2005).
Hampson, D. R. & Blatt, G. J. Autism spectrum disorders and neuropathology of the cerebellum. Front. Neurosci. https://doi.org/10.3389/fnins.2015.00420 (2015).
D’Mello, A. M. & Stoodley, C. J. Cerebro-cerebellar circuits in autism spectrum disorder. Front. Neurosci. https://doi.org/10.3389/fnins.2015.00408 (2015).
Prat, C. S., Stocco, A., Neuhaus, E. & Kleinhans, N. M. Basal ganglia impairments in autism spectrum disorder are related to abnormal signal gating to prefrontal cortex. Neuropsychologia 91, 268–281 (2016).
von Stechow, L. et al. The E3 Ubiquitin Ligase ARIH1 Protects against Genotoxic Stress by Initiating a 4EHP-Mediated mRNA Translation Arrest. Mol. Cell. Biol. 35, 1254–1268 (2015).
Aguilera, M., Oliveros, M., Martínez-Padrón, M., Barbas, J. A. & Ferrús, A. Ariadne-1: A Vital Drosophila Gene Is Required in Development and Defines a New Conserved Family of RING-Finger Proteins. Genetics 155, 1231–1244 (2000).
Elmehdawi, F. et al. Human Homolog of Drosophila Ariadne (HHARI) is a marker of cellular proliferation associated with nuclear bodies. Exp. Cell. Res. 319, 161–172 (2013).
Duda, D. M. et al. Structure of HHARI, a RING-IBR-RING Ubiquitin Ligase: Autoinhibition of an Ariadne-Family E3 and Insights into Ligation Mechanism. Structure 21, 1030–1041 (2013).
Greer, P. L. et al. The Angelman Syndrome Protein Ube3A Regulates Synapse Development by Ubiquitinating Arc. Cell 140, 704–716 (2010).
Vatsa, N. & Jana, N. R. UBE3A and Its Link With Autism. Front. Mol. Neurosci. https://doi.org/10.3389/fnmol.2018.00448 (2018).
Furlong, R. Refining the splice region. Nat. Rev. Genet. 19, 470–471 (2018).
Longo, F. & Klann, E. Reciprocal control of translation and transcription in autism spectrum disorder. EMBO Rep. https://doi.org/10.15252/embr.202052110 (2021).
Moynihan, T. P. et al. The Ubiquitin-conjugating Enzymes UbcH7 and UbcH8 Interact with RING Finger/IBR Motif-containing Domains of HHARI and H7-AP1. J. Biol. Chem. 274, 30963–30968 (1999).
Eisenhaber, B., Chumak, N., Eisenhaber, F. & Hauser, M.-T. The ring between ring fingers (RBR) protein family. Genome Biol. 8, 209 (2007).
Dove, K. K. et al. Structural Studies of HHARI/UbcH7∼Ub Reveal Unique E2∼Ub Conformational Restriction by RBR RING1. Structure 25, 890-900.e5 (2017).
Margolis, S. S. et al. EphB-mediated degradation of the RhoA GEF ephexin5 relieves a developmental brake on excitatory synapse formation. Cell 143, 442–455 (2010).
Sun, J. et al. UBE3A Regulates Synaptic Plasticity and Learning and Memory by Controlling SK2 Channel Endocytosis. Cell. Rep. 12, 449–461 (2015).
Giles, A. C. & Grill, B. Roles of the HUWE1 ubiquitin ligase in nervous system development, function and disease. Neural Dev. 15, 6 (2020).
Nordahl, C. W. Increased Rate of Amygdala Growth in Children Aged 2 to 4 Years With Autism Spectrum Disorders. Arch. Gen. Psychiatry 69, 53 (2012).
Parikshak, N. N. et al. Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism. Nature 540, 423–427 (2016).
Matoba, N. et al. Common genetic risk variants identified in the SPARK cohort support DDHD2 as a candidate risk gene for autism. Transl. Psychiatry 10, 265 (2020).
Fu, J. M. et al. Rare coding variation provides insight into the genetic architecture and phenotypic context of autism. Nat. Genet. 54, 1320–1331 (2022).
Mitra, I. et al. Patterns of de novo tandem repeat mutations and their role in autism. Nature 589, 246–250 (2021).
Tallantyre, E. & Robertson, N. P. Autism and intellectual disability. J. Neurol. 260, 936–939 (2013).
Li, M., Zhang, W. & Zhou, X. Identification of genes involved in the evolution of human intelligence through combination of inter-species and intra-species genetic variations. PeerJ 8, e8912 (2020).
Simó, S., Jossin, Y. & Cooper, J. A. Cullin 5 Regulates Cortical Layering by Modulating the Speed and Duration of Dab1-Dependent Neuronal Migration. J. Neurosci. 30, 5668–5676 (2010).
Scudder, S. L. & Patrick, G. N. Synaptic structure and function are altered by the neddylation inhibitor MLN4924. Mol. Cell. Neurosci. 65, 52–57 (2015).
Nakamura, T. et al. Topologically associating domains define the impact of de novo promoter variants on autism spectrum disorder risk. Cell. Genom. 4, 100488 (2024).
Lewis, C. M. & Vassos, E. Polygenic risk scores: from research tools to clinical instruments. Genome Med. 12, 44 (2020).
Vinci, M. et al. Exome sequencing in a child with neurodevelopmental disorder and epilepsy: Variant analysis of the AHNAK2 gene. Mol. Genet. Genomic Med. https://doi.org/10.1002/mgg3.2012 (2022).
Abbasi, A. & Alexandrov, L. B. Significance and limitations of the use of next-generation sequencing technologies for detecting mutational signatures. DNA Repair 107, 103200 (2021).
Tilemis, F.-N. et al. Germline CNV Detection through Whole-Exome Sequencing (WES) Data Analysis Enhances Resolution of Rare Genetic Diseases. Genes 14, 1490 (2023).
Chen, C., Qin, H., Tan, J., Hu, Z. & Zeng, L. The Role of Ubiquitin-Proteasome Pathway and Autophagy-Lysosome Pathway in Cerebral Ischemia. Oxid. Med. Cell. Longev. 2020, 1–12 (2020).
Zhang, L. et al. Dexmedetomidine Mitigated NLRP3-Mediated Neuroinflammation via the Ubiquitin-Autophagy Pathway to Improve Perioperative Neurocognitive Disorder in Mice. Front. Pharmacol. https://doi.org/10.3389/fphar.2021.646265 (2021).
Popovic, D., Vucic, D. & Dikic, I. Ubiquitination in disease pathogenesis and treatment. Nat. Med. 20, 1242–1253 (2014).
Lahiri, D. K., Bye, S., Nurnberger, J. I., Hodes, M. E. & Crisp, M. A non-organic and non-enzymatic extraction method gives higher yields of genomic DNA from whole-blood samples than do nine other methods tested. J. Biochem. Biophys. Methods 25, 193–205 (1992).
Chang, X. & Wang, K. wANNOVAR: annotating genetic variants for personal genomes via the web. J. Med. Genet. 49, 433–436 (2012).
Thorvaldsdottir, H., Robinson, J. T. & Mesirov, J. P. Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration. Brief. Bioinform. 14, 178–192 (2013).
Calì, F. et al. DXYS156: a multi-purpose short tandem repeat locus for determination of sex, paternal and maternal geographic origins and DNA fingerprinting. Int. J. Legal Med. 116, 133–138 (2002).
Richards, S. 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. 17, 405–424 (2015).
Kopanos, C. et al. VarSome: the human genomic variant search engine. Bioinformatics 35, 1978–1980 (2019).
Shihab, H. A. et al. Predicting the Functional, Molecular, and Phenotypic Consequences of Amino Acid Substitutions using Hidden Markov Models. Hum. Mutat. 34, 57–65 (2013).
Lin, H. et al. RegSNPs-intron: a computational framework for predicting pathogenic impact of intronic single nucleotide variants. Genome Biol. 20, 254 (2019).
Pontén, F., Schwenk, J. M., Asplund, A. & Edqvist, P.-H.D. The Human Protein Atlas as a proteomic resource for biomarker discovery. J. Intern. Med. 270, 428–446 (2011).
Wang, M. & Marín, A. Characterization and prediction of alternative splice sites. Gene 366, 219–227 (2006).
Tang, R., Prosser, D. O. & Love, D. R. Evaluation of Bioinformatic Programmes for the Analysis of Variants within Splice Site Consensus Regions. Adv. Bioinform. 2016, 1–10 (2016).
Scalzitti, N. et al. Spliceator: multi-species splice site prediction using convolutional neural networks. BMC Bioinform. 22, 561 (2021).
Pollard, K. S., Hubisz, M. J., Rosenbloom, K. R. & Siepel, A. Detection of nonneutral substitution rates on mammalian phylogenies. Genome Res. 20, 110–121 (2010).
Schwarz, J. M., Rödelsperger, C., Schuelke, M. & Seelow, D. MutationTaster evaluates disease-causing potential of sequence alterations. Nat. Methods 7, 575–576 (2010).
Montenegro, L. R., Lerário, A. M., Nishi, M. Y., Jorge, A. A. L. & Mendonca, B. B. Performance of mutation pathogenicity prediction tools on missense variants associated with 46 XY differences of sex development. Clinics 76, e2052 (2021).
Frías-López, C. et al. DOMINO: development of informative molecular markers for phylogenetic and genome-wide population genetic studies in non-model organisms. Bioinformatics 32, 3753–3759 (2016).
Quinodoz, M. et al. DOMINO: Using Machine Learning to Predict Genes Associated with Dominant Disorders. Am. J. Hum. Genet. 101, 623–629 (2017).
Stenson, P. D. et al. The Human Gene Mutation Database (HGMD®): Optimizing its use in a clinical diagnostic or research setting. Hum. Genet. 139, 1197–1207 (2020).
Crosara, K. T. B., Moffa, E. B., Xiao, Y. & Siqueira, W. L. Merging in-silico and in vitro salivary protein complex partners using the STRING database: A tutorial. J. Proteomics 171, 87–94 (2018).
Meng, E. C. et al. UCSF ChimeraX : Tools for structure building and analysis. Protein Sci. https://doi.org/10.1002/pro.4792 (2023).
Acknowledgements
Special acknowledgements for this paper are due to Eleonora Di Fatta for her valuable assistance in the translation, preparation and formatting of the text. . We would like to thank Angelo Gloria, Alda Ragalmuto, and Valeria Chiavetta for their technical contribution.
Funding
This work was partially supported by the Italian Ministry of Health “Ricerca Corrente 2017–2023” and 5xmille.
Author information
Authors and Affiliations
Contributions
Conceptualization: M.V, S.T, F.C.; methodology: M.V, R.G.R, V.T., M.E.; validation: M.V., S.T., R.G.R., F.C.; investigation: M.V., S.T., R.G.R., A.M., V.T., C.F., S.S., M.E., F.C.; data curation: M.V.., S.T., M.E., F.C.; original draft preparation: M.V., S.T., A.M., S.S., M.E., F.C.; manuscript review and editing: M.V., S.T., S.S., M.E., F.C.; supervision: M.V., S.T., S.S., F.C All authors have read and agreed to the final version of the manuscript.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Publisher's note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Vinci, M., Treccarichi, S., Galati Rando, R. et al. A de novo ARIH2 gene mutation was detected in a patient with autism spectrum disorders and intellectual disability. Sci Rep 14, 15848 (2024). https://doi.org/10.1038/s41598-024-66475-2
Received:
Accepted:
Published:
DOI: https://doi.org/10.1038/s41598-024-66475-2
- Springer Nature Limited