Genetic Variants and Phenotypic Data Curated for the CAGI6 Intellectual Disability Panel Challenge

doi:10.21203/rs.3.rs-5267762/v1

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Genetic Variants and Phenotypic Data Curated for the CAGI6 Intellectual Disability Panel Challenge

https://doi.org/10.21203/rs.3.rs-5267762/v1

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Neurodevelopmental disorders (NDDs) are common conditions including clinically diverse and genetically heterogeneous diseases, such as intellectual disability, autism spectrum disorders, and epilepsy. The intricate genetic underpinnings of NDDs pose a formidable challenge, given their multifaceted genetic architecture and heterogeneous clinical presentations. This work delves into the intricate interplay between genetic variants and phenotypic manifestations in neurodevelopmental disorders, presenting a dataset curated for the Critical Assessment of Genome Interpretation (CAGI6) ID Panel Challenge. The CAGI6 competition serves as a platform for evaluating the efficacy of computational methods in predicting phenotypic outcomes from genetic data.

In this study, a targeted gene panel sequencing has been used to investigate the genetic causes of NDDs in a cohort of 415 paediatric patients. We identified 60 pathogenic/likely pathogenic and 49 variants of Uncertain Significance (VUSs) in 102 individuals that accounted for 25% of NDD cases in the cohort. The most mutated genes were ANKRD11, MECP2, ARID1B, ASH1L, CHD8, KDM5C, MED12 and PTCHD1 The majority of pathogenic variants were de novo, with some inherited from mildly affected parents. Loss-of-function variants were the most common type of pathogenic variant. In silicoanalysis tools were used to assess the potential impact of variants on splicing and structural/functional effects of missense variants. The study highlights the challenges in variant interpretation especially in cases with atypical phenotypic manifestations. Overall, this study provides further insights into the genetic causes of NDDs and emphasises the importance of understanding the underlying genetic factors for accurate diagnosis, and intervention development in neurodevelopmental conditions.

Neurodevelopmental Disorders

gene-panel

CAGI

de novo variants

ANKRD11

ASH1L

The field of neurodevelopmental disorders (NDDs) encompasses a diverse group of conditions characterised by impairments in cognitive, motor, and social functions that arise early in development. The study of the genetic causes of NDDs is complicated by its extensive genetic and phenotypic heterogeneity, in addition to a high degree of comorbidity (Morris-Rosendahl & Crocq, 2020). The increased co-occurrence of these disorders, which include (among others) intellectual disability, autism spectrum disorder, language/speech disorders and epilepsy, suggested shared genetic aetiology among NDDs (Jensen & Girirajan, 2017). Multiple genetic mechanisms can result in overlapping NDD phenotypes and, simultaneously, a single genetic mechanism can result in a range of phenotypic outcomes (Parenti et al., 2020). Understanding the underlying genetic causes of NDDs is crucial for accurate diagnosis, prognosis, and the development of targeted interventions.

Technological advances in genomics have enabled the identification of a huge amount of rare genetic data from both general population cohorts (e.g. Genome Aggregation Database) (Karczewski et al., 2020) as well as particular diseases (e.g., Autism Spectrum Disorders) (Feliciano et al., 2019; Zhou et al., 2022). The aggregation and sharing of phenotypic and genetic data through public or restricted-access databases and international collaborative efforts has led to a remarkable progress in the understanding of the genetic architecture and neurobiology underlying NDDs (Cousin et al., 2022; Fu et al., 2022; Gehin et al., 2023; Satterstrom et al., 2020). Many studies highlighted the contribution of de novo variants in the NDD liability model (Coe et al., 2019; Iossifov et al., 2014; Kaplanis et al., 2020; Krumm et al., 2015; Satterstrom et al., 2020). On the other hand, many NDD cases appear to result from the effects of a polygenic inheritance mode, in which the burden of de novo, inherited rare and common variants in multiple genes all contribute to the phenotype (Fu et al., 2022; Grove et al., 2019; Zhou et al., 2022). Rare genetic variations, particularly truncating variants, have played a crucial role in the characterization of hundreds of NDD-related genes (Deciphering Developmental Disorders Study, 2017). Although the presence of missense variants in disease genes can be indicative of their deleteriousness, the significance of many missense variants remains uncertain due to position-specific effects (Quinodoz et al., 2022).

In a previous study, we presented the findings obtained with the application of a targeted gene panel sequencing in a paediatric cohort of 150 NDD individuals (Aspromonte et al., 2019). Overall, this study provided a valuable guide for the interpretation of genetic variants, based on expert knowledge related to the disease phenotype and gene functions. The description of diagnosed cases highlighted the critical steps of variant interpretation in the clinical diagnostic context of neurodevelopmental conditions. With this dataset of genetic and phenotypic data from 150 individuals, we participated in the Fifth edition of the Critical Assessment of Genome interpretation (CAGI5). CAGI is a worldwide blind test to assess computational methods for predicting phenotypic impacts of genomic variations (Critical Assessment of Genome Interpretation Consortium, 2024). Our data have been used as the “ID panel challenge” dataset to assess computational approaches aiming to predict comorbid phenotypes from genetic variants in a subset of NDD genes (Carraro et al., 2019). The participation of the four predictor groups in this experiment provided a basis for the development of improved methods as well as for designed and automated use in clinical settings (J. Chen, 2019; Critical Assessment of Genome Interpretation Consortium, 2024).

In this study we present the genetic and phenotypic data as well as the findings of the same 74 gene panel sequencing obtained on a larger cohort of 415 NDD patients. This dataset has been used in a new “ID panel challenge” of the sixth edition of CAGI (CAGI6). Here, the CAGI5 sequence data, patient’s phenotype and a list of selected variants was made available to help the predictors for training their methods. Like in the previous study (Aspromonte et al., 2019), here we describe the diagnosed cases that could explain the difficulties in variant interpretation and in predicting the associated phenotypes.

Patient selection

The 415 cases of this cohort were selected from those referred to the Laboratory of Molecular Genetic of Neurodevelopmental Disorders, University Hospital of Padua (Italy), from March 2017 to June 2019, for gene panel testing. Clinical data were collected by the referring clinicians/geneticists from 17 Italian public hospitals with a standardised clinical record describing family history, clinical phenotype, previous genetics, metabolic and neurophysiological investigations. Table 1 summarises the clinical data of the patients, while Supplementary Table S1 reports for each of 415 patients the presence of ID (HP:0001249), ASD (HP:0000729), epilepsy (HP:0001250), microcephaly (HP:0000252) or macrocephaly (HP:0000256), hypotonia (HP:0001252), and ataxia (HP:0001251). Each phenotype was intended to follow the criteria defined by the corresponding Human Phenotype Ontology (HPO) terms (Köhler et al., 2017). Written informed consent was obtained from the patient’s parents or legal representative.

Table 1

Description of the cohort of 415 individuals enrolled for the CAGI6 ID panel challenge. The table includes demographic information, clinical features as well as results from genetic and neurological investigations. *Abbreviations*: ASD: autism spectrum disorder; aCGH: array-comparative genomic hybridization; EEG: electroencephalogram; MRI: magnetic resonance imaging; X-linked: variants in genes located on X-chromosome.
Features	Patients (n = 415)
Gender
Female	147 (35%)
Male	268 (65%)
Total	415
Age (year old, at diagnosis)
[0–10]	277 (67%)
[11–20]	122 (29%)
> 20	16 (4%)
Familial History
Sporadic	320 (77%)
Familial	95 (23%)
Sib pair	24 (6%)
X-linked	2 (0.5%)
Intellectual Disability
Total reported	352 (84.8%)
Mild	109 (31%)
Mild/Moderate, Moderate	100 (28%)
Severe	70 (20%)
Not evaluated	73 (21%)
Not reported	53 (12.8%)
Normal cognitive function	10 (2.4%)
Comorbidity
ASD (autistic features)	205 (49%)
ASD not reported	62 (15%)
Epilepsy	84 (20%)
Hypotonia	71 (17%)
Ataxia	30 (7%)
Microcephaly	45 (11%)
Macrocephaly	40 (10%)
Other investigation
aCGH	338 (82%)
X-Fragile	217 (52%)
Other genetic tests (single genes, gene panels)	84 (20%)
EEG anomaly	99 (24%)
MRI anomaly	84 (20%)

Gene panel sequencing and data analysis

We sequenced 74 genes in DNA samples from 415 paediatric patients with NDDs. The sequencing was performed using the Ion Torrent platform at the Laboratory of Padua as previously described in (Aspromonte et al., 2019). We designed a cost-effective targeted panel using Ion AmpliSeq™ Designer, to amplify all exons and flanking regions (10 bp) of 74 genes associated with ID and ASD comorbidities (Supplementary Table 3). To create a variant in-house database, we developed a pipeline to annotate the variants using ANNOVAR (Wang et al., 2010; Yang & Wang, 2015) and calculate the frequency of each variant within our dataset. The variants were filtered based on sequencing parameters, frequency in the general population (eg. gnomAD v4.1.0) (S. Chen et al., 2022) and in the in-house database, and pathogenicity predictions. Segregation analysis was conducted using Sanger sequencing when DNA samples from relatives were available. For de novo variants, paternity and maternity were confirmed as described before (Aspromonte et al., 2019). For variants detected on X-linked genes, the X-inactivation pattern was assessed on the human androgen receptor (AR) gene locus. When possible, intron and splicing variants were analysed using mRNA extracted from patient peripheral blood leukocytes through reverse transcription of cDNA.Variant interpretation followed the criteria outlined by the American College of Medical Genetics and Genomics (ACMG) (Richards et al., 2008). For the final classification of the identified variants we used the same workflow used for CAGI5 challenge, a detailed description has been published in Aspromonte et al (Aspromonte et al., 2019).

The only change is in the naming of the variant classes. We now refer to them according to the ACMG guidelines, using 'pathogenic' instead of 'disease-causing.' Additionally, the class previously defined as 'contributing factor' is now called 'risk factor.

In silico analysis of the variants

The potential impact on splicing signals has been evaluated by Human Splicing Finder (Desmet et al., 2009). Pathogenicity of missense variants has been predicted using computational methods provided by ANNOVAR (Yang & Wang, 2015) and Combined Annotation Dependent Depletion (CADD) (Rentzsch et al., 2019). Conservation of mutated positions has been evaluated with GERP++ (Davydov et al., 2010). Structural effects of missense variants for GRIN2A, SLC6A1, ANKRD11, IQSEC2 have been evaluated using the structures deposited in the Protein Data Bank database (https://www.rcsb.org/) (Berman et al., 2000; Burley et al., 2023) (PDB codes: 6IRA; 7SK2; 6FAE) or the AlphaFold models (Jumper et al., 2021). Variants were mapped and visualised on their respective structures using Pymol Molecular Graphics System Version (Schrödinger, LLC, 2021).

Protein sequences, retrieved from the UniProtKB database (UniProt Consortium, 2023), have been aligned with MAFFT (Katoh & Standley, 2013) and visualised with Jalview. Secondary structure and amino-acid enrichment has been predicted by FELLS (Piovesan et al., 2017), while the MobiDB (Piovesan et al., 2023), DisProt (Aspromonte et al., 2023) and ELM (Kumar et al., 2023) resources have been used to predict or retrieve information of intrinsically disordered regions (IDRs) and functional linear motifs, respectively.

Cohort description

A total of 415 paediatric patients with Neurodevelopmental Disorders (NDDs) were included in this study. The cohort primarily consisted of 268 males (65%) and patients under 20 years of age (96%) (Table 1). 320 (77%) were sporadic cases, however a family history for NDDs was reported in 95 (23%) cases, with affected siblings in 6%. Intellectual Disability (ID) was the most common clinical feature, reported in 84.8% of cases, with a higher proportion of mild to moderate forms. While only 20% of the cases were reported with a severe intellectual impairment. IQ level was not evaluated in 73 cases with ID (21%). Only ten patients (2.4%) presented a normal Intellectual Quotient (IQ), while information regarding cognitive impairment was not reported in 53 (12.8%) children (Table 1). Autism Spectrum Disorder (ASD) was reported in 49% of patients, with 40% of them also having ID. Epilepsy, ataxia, microcephaly, and macrocephaly were fewer common phenotypes. At least one clinical trait was present in each patient, and complete information for all seven phenotypic traits was available for 47% of cases. Despite various genetic analyses, most patients remained undiagnosed. Two patients with chromosomal alterations, XXX and XXY karyotype, were diagnosed with Trisomy X and Klinefelter syndrome, respectively (UniPD_0267 and UniPD_0284).

Mutated genes and variants type

The low-cost targeted gene-panel designed for ID/ASD enabled us to obtain high-quality sequencing data, with a coverage > 100x in the targeted regions. In our cohort we identified 60 pathogenic/likely pathogenic variants (Table 2) and 49 Variants of Uncertain Significance (VUS) (Table 3). The reported variants map to 45 different genes (Fig. 1). For 16 genes, variants were detected in more than two patients. ANKRD11 was the most frequently mutated gene, with seven detected variants. MECP2 variants were found in six individuals, and ARID1B, ASH1L, CHD8, KDM5C, MED12 and PTCHD1 each had variants in five cases. Out of the 60 (14.5%) patients with pathogenic/likely pathogenic variants, 18 had a reported family history, 17 patients were sporadic, while family information was unavailable for 25 patients. Most of the pathogenic variants (n = 44; 73%) were de novo, three inherited from mildly affected parents, three were not inherited from the single available parent, and for 16.6% (n = 10) of the variants, inheritance could not be assessed (Table 1). The majority of pathogenic variants, 36 out of 60, are loss-of-function (LoF) variants. Specifically, 16 introduce a novel stop codon, 20 are frameshift insertions or deletions, and 22 variants are missense. Among them we identified the somatic mosaicism variant p.(Arg504Gln) in GRIN2A. Targeted next generation sequencing on the proband’s blood sample and oral mucosa cells allowed for the estimation of a mosaicism of 25% (Fig. 2). Additionally, we identified a novel de novo non-frameshift substitution variant in the DEAF1 gene p.(Pro237_Thr238delinsSerSer) and one de novo deep intronic variant (c.4956-17A > G) in MED13L which impacts the splicing mechanism (Fig. 3). Most pathogenic and likely pathogenic variants were identified in patients whose clinical phenotype matched the mutated gene. In other individuals, we observed clinical features that were atypical for the mutated genes (Table 4).

Table 2

Pathogenic/Likely Pathogenic variants found in 415 paediatric patients.
P	S	GENE	INH	ZYG	VFS	FH	Type	Ref Seq	Variant	dbSNP	Clinvar	MAF	CP	CADD	GERP
0107	F	ADNP	AD	HT	DN	-	MIS	NM_001282531.3	c.2473G > C p.(Gly825Arg)	-	-	-	8	25	5.1
0129	M	ADNP	AD	HT	-	-	FS	NM_001282531.3	c.2232_2236del p.(Glu744AspfsTer2)	-	-	-	-	.	.
0072	M	ADNP	AD	HT	DN	-	FS	NM_001282531.3	c.539_542del p.(Val180GlyfsTer17)	rs1057518345	P	-	-	.	.
0291	M	ANKRD11	AD	HT	DN	-	MIS	NM_013275.6	c.7606C > T p.(Arg2536Trp)	rs2151701893	P/LP	-	9	29	1.7
0256	M	ANKRD11	AD	HT	DN	-	FS	NM_013275.6	c.5973_5997del p.(Lys1992SerfsTer87)	-	-	-	-	.	.
0205	F	ANKRD11	AD	HT	DN	-	FS	NM_013275.6	c.4396_4397del p.(Arg1466GlyfsTer87)	-	-	-	-	.	.
0171	F	ANKRD11	AD	HT	-	-	STOP	NM_013275.6	c.2446G > T p.(Glu816Ter)	-	-	-	-	37	5.7
0212	F	ANKRD11	AD	HT	DN	-	FS	NM_013275.6	c.2165_2166del p.(Lys722ArgfsTer19)	-	-	-	-	.	.
0330	F	ANKRD11	AD	HT	Absent in healthy sister	-	FS	NM_013275.6	c.1903_1907del p.(Lys635GlnfsTer26)	rs886041125	P	-	-	.	.
0242	M	ANKRD11	AD	HT	DN	-	FS	NM_013275.6	c.281_284del p.(Ala94GlyfsTer29)	-	-	-	-	.	.
0142	F	ARID1B	AD	HT	-	-	STOP	NM_001374828.1	c.1996C > T p.(Gln666Ter)	rs1554265250	-	-	-	40	5.5
0105	F	ARID1B	AD	HT	DN	-	STOP	NM_001374828.1	c.3673C > T p.(Arg1225Ter)	rs387907141	P	-	-	40	5.0
0408	F	ARID1B	AD	HT	DN	-	FS	NM_001374828.1	c.4964_4974del p.(Ile1655ThrfsTer100)	-	-	-	-	.	.
0093	M	ARID1B	AD	HT	DN	-	MIS	NM_001374828.1	c.6775T > C p.(Ser2259Pro)	rs1057521854	LP	-	7	27	5.5
0141	M	ASH1L	AD	HT	DN	-	MIS	NM_018489.3	c.3893T > G p.(Leu1298Arg)	-	-	-	11	26	4.9
0337	M	ASH1L	AD	HT	DN	-	MIS	NM_018489.3	c.3179A > G p.(Asn1060Ser)	rs1665817487	-	-	6	23	5.1
0390	M	CHD8	AD	HT	-	-	FS	NM_001170629.2	c.7148del p.(Pro2383GlnfsTer47)	-	-	-	-	.	.
0393	F	CHD8	AD	HT	DN	-	MIS	NM_001170629.2	c.6997C > T p.(Arg2333Cys)	rs1887539639	-	-	6	32	5.4
0336	F	CHD8	AD	HT	DN	-	MIS	NM_001170629.2	c.2282G > T p.(Trp761Leu)	.	-	-	11	29	5.0
0062	M	CHD8	AD	HT	DN	-	STOP	NM_001170629.2	c.1174C > T p.(Gln392Ter)	rs1555318204	-	-	-	36	5.4
0246	M	CTNNB1	AD	HT	-	-	FS	NM_001904.4	c.160dup p.(Glu54GlyfsTer12)	-	-	-	-	.	.
0395	F	DEAF1	AD/AR	HT	DN	-	MIS	NM_021008.4	c.782G > C p.(Arg261Pro)	-	-	-	11	25	4.5
0172	F	DEAF1	AD/AR	HT	DN	-	nonFS	NM_021008.4	c.709_712delinsTCCT p.(Pro237_Thr238delinsSerSer)	-	-	-	-	.	.
0362	M	DYRK1A	AD	HT	DN	-	STOP	NM_001347721.2	c.427G > T p.(Gly143Ter)	rs1463551651	-	-	-	37	5.2
0331	F	DYRK1A	AD	HT	DN	-	STOP	NM_001347721.2	c.664C > T p.(Arg222Ter)	rs780441716	P	-	-		5.6
0112	M	EHMT1	AD	HT	DN	-	MIS	NM_024757.5	c.3186C > G p.(Cys1062Trp)	-	-	-	11	23	0.1
0399	M	FOXP1	AD	HT	DN	-	STOP	NM_001349338.3	c.1630C > T p.(Arg544Ter)	-	P	-	-	38	4.0
0351	M	FOXP1	AD	HT	DN	-	FS	NM_001349338.3	c.1590dup p.(Gly531ArgfsTer8)	-	-	-	-	.	.
0407	F	FOXP1	AD	HT	DN	-	STOP	NM_001349338.3	c.1526G > A p.(Trp509Ter)	rs780157776	-	-	-	47	5.9
0286	M	GATAD2B	AD	HT	DN	-	MIS	NM_020699.4	c.922T > G p.(Cys308Gly)	-	-	-	3	23	5.1
0010	F	GRIN2A	AD	MOS	DN	-	MIS	NM_001134407.3	c.1511G > A p.(Arg504Gln)	rs1331671132	VUS	-	6	24	5.3
0110	F	KDM5C	XL	HT	DN	-	MIS	NM_004187.5	c.3794T > C p.(Leu1265Pro)	-	-	-	9	27	4.8
0243	M	KDM5C	XL	HE	MAT	-	STOP	NM_004187.5	c.2851C > T p.(Arg951Ter)	rs1556837277	P	-	-	36	3.8
0366	F	KDM5C	XL	HT	DN	-	MIS	NM_004187.5	c.1795C > T p.(Arg599Cys)	rs1556842184	LP	-	9	29	5.7
0388	M	MBD5	AD	HT	DN	-	FS	NM_001378120.1	c.24del p.(Asp8GlufsTer75)	-	-	-	-	.	.
0140	F	MECP2	XL	HT	DN	-	STOP	NM_004992.4	c.808C > T p.(Arg270Ter)	rs61750240	P	-	-	37	.
0267	F	MECP2	XL	XXX	-	-	STOP	NM_004992.4	c.808C > T p.(Arg270Ter)	rs61750240	P	-	-	37	3.7
0411	F	MECP2	XL	HT	-	-	STOP	NM_004992.4	c.763C > T p.(Arg255Ter)	rs61749721	P	-	-	38	3.5
0118	F	MECP2	XL	HT	-	-	MIS	NM_004992.4	c.473C > T p.(Thr158Met)	rs28934906	P/LP	-	11	27	5.5
0081	F	MECP2	XL	HT	-	-	MIS	NM_004992.4	c.316C > T p.(Arg106Trp)	rs28934907	P/LP	-	12	26	2.8
0210	M	MED12	XLD	HE	-	+	MIS	NM_005120.3	c.4147G > A p.(Ala1383Thr)	rs863223696	P	-	9	29	4.4
0383	M	MED13L	AD	HT	DN	-	SP	NM_015335.5	c.4956-17A > G p.Ser1652Argfs*1	-	-	-	-	.	.
0014	M	PHF21A	AD	HT	DN	-	FS	NM_001352027.3	c.1032_1035del p.(Thr345ArgfsTer28)	rs2092369866	P	-	-	.	.
0056	M	PPP2R5D	AD	HT	DN	-	MIS	NM_006245.4	c.598G > A p.(Glu200Lys)	rs863225079	P/LP	-	9	32	5.7
0169	F	PTCHD1	XL	HT	DN	-	MIS	NM_173495.3	c.2072G > A p.(Arg691Gln)	rs1569143368	-	-	5	23	5.3
0104	M	PTCHD1	XL	HE	MAT	+	STOP	NM_173495.3	c.2289C > A p.(Tyr763Ter)	-	-	-	-	35	3.4
0109	M	PTEN	AD	HT	DN	-	MIS	NM_000314.8	c.103A > G p.(Met35Val)	rs876659443	P	-	12	25	5.2
0309	M	SATB2	AD	HT	DN	-	FS	NM_001172509.2	c.1105_1106insT p.(Arg369MetfsTer3)	-	-	-	-	.	.
0240	M	SETBP1	AD	HT	DN	-	STOP	NM_015559.3	c.1765C > T p.(Arg589Ter)	rs1568235086	P/LP	-	-	39	6.1
0418	F	SHANK2	AD	HT	DN	-	FS	NM_133266.5	c.2989_3004del p.(Pro997SerfsTer38)	-	-	-	-	.	.
0333	F	SHANK3	AD	HT	DN	-	FS	NM_0033517.1	c.4637_4638del p.(Phe1563GlnfsTer5)	-	-	-	-	.	.
0114	M	SLC6A1	AD	HT	NOT MAT	-	MIS	NM_003042.4	c.855G > T p.(Trp285Cys)	-	-	-	11	31	4.9
0047	M	SLC6A1	AD	HT	DN	-	MIS	NM_003042.4	c.919G > A p.(Gly307Arg)	rs1553689696	P/LP	-	11	26	4.8
0034	M	SLC6A1	AD	HT	MAT	+	MIS	NM_003042.4	c.1084G > A p.(Gly362Arg)	rs1131691302	LP	-	11	25	4.9
0299	F	SYNGAP1	AD	HT	DN	-	FS	NM_006772.3	c.431_434del p.(Thr144SerfsTer29)	-	-	-	-	.	.
0170	M	SYNGAP1	AD	HT	DN	-	FS	NM_006772.3	c.2473_2474dup p.(Asp826ArgfsTer11)	-	-	-	-	.	.
0288	F	SYNGAP1	AD	HT	DN	-	FS	NM_006772.3	c.3778_3779del p.(Lys1260GlufsTer22)	-	-	-	-	.	.
0200	F	UBE3A	AD	HT	DN	-	FS	NM_130839.5	c.2571_2574dup p.(Leu859GlufsTer23)	-	-	-	-	.	.
0391	M	WAC	AD	HT	DN	-	STOP	NM_016628.5	c.139C > T p.(Arg47Ter)	rs368543869	P	-	-	36	3.7
0148	F	WAC	AD	HT	NOT PAT	-	STOP	NM_016628.5	c.374C > A p.(Ser125Ter)	rs864321692	P	-	-	38	5.8

Abbreviations: P, patient code; S, sex; INH, mode of inheritance; ZYG, zygosity; VFS, Variant Family Segregation; FH, familial history; Ref Seq, reference sequence; MAF, minor allele frequency; CP. consensus prediction among 12 computational tools provided by Annovar; CADD, Combined Annotation Dependent Depletion score; GERP, genomic evolutionary rate profiling score; M, Male; F, Female; AD, autosomal dominant; AR, autosomal recessive; XL, X-linked; HT, heterozygous; HE, hemizygous; MOS, mosaicism; DN, de novo; MAT, maternal; PAT, paternal; MIS, missense; FS, frameshift; P, pathogenic; LP, likely pathogenic

Table 3

Variants of Uncertain Significance found in 415 paediatric patients.
P	S	GENE	INH	ZYG	VFS	XCI	Type	Ref Seq	Variant	dbSNP	Clinvar	MAF	CP	CADD	GERP	HSF
215	M	AP1S2	XL	HE	-	-	SYN	NM_003916.5	c.240G > A p.(Leu80Leu)	rs912444495	-	-	-	-	-	ESE site broken, New cryptic acceptor site
222	M	ARID1B	AD	HT	-	-	MIS	NM_001374828.1	c.1031C > T p.(Pro344Leu)	-	-	-	5	24.8	2.78	-
385	M	ASH1L	AD	HT	-	-	MIS	NM_018489.3	c.2950C > T p.(Arg984Cys)	rs548853139	-	0.00002005	10	27.2	5.16	-
385	M	FOXP1	AD	HT	-	-	MIS	NM_001349338.3	c.1667T > C p.(Ile556Thr)	rs751381124	-	0.000003976	7	24.3	6.13	-
19	M	ASH1L	AD	HT	-	-	MIS	NM_018489.3	c.6916C > T p.(Arg2306Trp)	rs142371619	-	7.311e-05	11	31	4.96	-
400	F	ASH1L	AD	HT	-	-	MIS	NM_018489.3	c.7543C > T p.(Arg2515Trp)	rs747531593	-	0.00001996	9	32	2.74	-
84	M	ATRX	XL	HE	MAT	MAT, 32:68	MIS	NM_000489.6	c.4196A > G p.(Glu1399Gly)	-	-	-	9	24.5	5.24	-
296	M	ATRX	XL	HE	MAT	MAT, 26:74	MIS	NM_000489.6	c.4407T > A p.(Asp1469Glu)	-	-	-	8	22.5	2.46	-
359	M	CASK	XL	HE	MAT	random	MIS	NM_001367721.1	c.44G > A p.(Cys15Tyr)	-	-	-	5	23.9	4.88	-
127	M	CASK	XL	HE	MAT	MAT, 32:68	MIS	NM_001367721.1	c.2640C > A p.(Asp880Glu)	-	-	-	3	12.3	0.197	-
374	M	CHD8	AD	HT	-	-	MIS	NM_001170629.2	c.203C > A p.(Pro68His)	-	-	-	4	23.5	4.78	-
273	F	CNTNAP2	AD/AR	HT	PAT	-	MIS	NM_014141.6	c.511C > T p.(Arg171Cys)	rs375032955	VUS	4.47E-02	11	25.7	5.47	-
273	F	CNTNAP2	AD/AR	HT	MAT	-	SYN	NM_014141.6	c.2517T > C p.(Asn839=)	rs143358892	LB	0.00007075	-	-	-	-
268	M	CNTNAP2	AD/AR	HT	-	-	MIS	NM_014141.6	c.2368C > A p.(Arg790Ser)	rs200089329	VUS	-	8	27	5.6	-
223	M	DEAF1	AD/AR	HT	-	-	SP?	NM_021008.4	c.805-31C > G p.?	-	-	-	-	-	-	Broken Branch Point
401	F	DEAF1	AD/AR	HT	-	-	MIS	NM_021008.4	c.908G > T p.(Arg303Leu)	-	VUS	-	9	28.6	3.65	-
401	F	KATNAL2	AD	HT	-	-	MIS	NM_001387690.1	c.1084A > G p.(Arg362Gly)	-	-	-	12	29.6	4.8	-
330	F	EHMT1	AD	HT	healthy sister negative	-	MIS	NM_024757.5	c.103G > A p.(Asp35Asn)	rs371134699	VUS	0.00003081	9	25.3	5.41	-
170	M	GRIA3	XL	HE	MAT	MAT,74:26	MIS	NM_000828.5	c.2053G > A p.(Gly685Ser)	-	-	-	6	25.3	5:45	-
345	M	GRIK2	AD/AR	HT	-	-	MIS	NM_021956.5	c.205A > G p.(Thr69Ala)	-	VUS	8.154e-06	7	22	5.67	-
380	F	GRIN2A	AD	HT	-	-	MIS	NM_001134407.3	c.3163G > C p.(Glu1055Gln)	rs370107080	VUS	0.00001591	8	26.1	5.33	-
378	M	GRIN2B	AD	HT	-	-	MIS	NM_000834.5	c.2557G > A p.(Val853Ile)	rs201477697	-	-	4	26	5.76	-
179	F	GRIN2B	AD	HT	-	-	MIS	NM_000834.5	c.4259A > G p.(Asp1420Gly)	-	-	-	6	27	5.23	-
59	M	IL1RAPL1	XL	HE	MAT	-	MIS	NM_014271.4	c.735G > C p.(Leu245Phe)	-	-	-	4	21.2	4.14	-
160	F	IQSEC2	XL	HT	-	-	MIS	NM_001111125.3	c.322C > T p.(His108Tyr)	-	-	-	4	23.4	2.81	-
85	F	IQSEC2	XL	HT	-	98:2	SYN	NM_001111125.3	c.999G > A p.(Lys333=)	-	-	-	-	-	-	Alteration of the WT Donor site
152	M	IQSEC2	XL	HE	MAT	MAT,67:33	MIS	NM_001111125.3	c.2976G > T p.(Leu992Phe)	-	-	-	5		2.21	-
279	M	KDM5C	XL	HE	MAT	MAT,71:29	MIS	NM_004187.5	c.835G > C p.(Gly279Arg)	-	VUS	-	2	12.88	1:28	-
353	M	KDM5C	XL	HE	-	-	MIS	NM_004187.5	c.1259T > C p.(Leu420Pro)	-	-	-	12	29.7	5.85	-
413	F	KIRREL3	AD	HT	-	-	MIS	NM_032531.4	c.1639G > A p.(Ala547Thr)	-	-	0.000004013	7	24.8	5.46	-
388	M	MECP2	XL	HE	MAT	MAT,64:36	MIS	NM_004992.4	c.1231A > G p.(Ser411Gly)	-	-	-	3	19.81	4.22	-
174	M	MED12	XL	HE	MAT	MAT,76:24	MIS	NM_005120.3	c.1994C > G p.(Ser665Cys)	rs764981858	VUS	0.00001104	8	24.2	4.49	-
51	M	MED12	XL	HE	DN	-	SYN	NM_005120.3	c.3909C > T p.(Asp1303=)	-	-	-	.	.	.	Altered ESE / ESS motifs ratio (-5)
155	F	MED12	XL	HT	-	-	MIS	NM_005120.3	c.4888G > A p.(Asp1630Asn)	-	VUS	-	4	23.2	4.15	-
283	M	MED12	XL	HE	MAT	MAT,60:40	MIS	NM_005120.3	c.5095C > G p.(Pro1699Ala)	-	-	-	10	24	4.17	-
390	M	MED13L	AD	HT	-	-	MIS	NM_015335.5	c.1367C > G p.(Ser456Cys)	-	-	-	6	22.5	5.76	-
234	M	PPP2R5D	AD	HT	-	-	NONFS	NM_006245.4	c.123_140del p.(Pro42_Gln47del)	-	-	-	-	-	-	-
21	F	PPP2R5D	AD	HT	-	-	MIS	NM_006245.4	c.1606A > T p.(Thr536Ser)	-	-	-	4	22.6	5.37	-
420	M	PQBP1	XL	HE	MAT	MAT,73:28	MIS	NM_005710.2	c.530G > A p.(Arg177His)	-	VUS	-	7	27	4.13	-
402	M	PTCHD1	XL	HE	-	-	MIS	NM_173495.3	c.605G > A p.(Arg202Gln)	rs771036286	-	0.000005453	5	22	3.99	-
149	M	PTCHD1	XL	HE	MAT	random	MIS	NM_173495.3	c.751C > T p.(Pro251Ser)	rs368662150	VUS	0.000005449	5	18.37	4.86	-
415	M	PTCHD1	XL	HE	MAT	MAT,37:63	MIS	NM_173495.3	c.1624A > G p.(Thr542Ala)	-	-	-	5	20.4	5.69	-
153	M	SCN2A	AD	HT	-	-	MIS	NM_001040142.2	c.2496C > A p.(Ser832Arg)	-	-	-	12	25.1	5.59	-
360	M	SLC9A6	XL	HE	-	-	MIS	NM_001042537.2	c.1034C > T p.(Thr345Ile)	-	-	-	8	27.9	5.35	-
111	M	SYNGAP1	AD	HT	-	-	MIS	NM_006772.3	c.1003C > T p.(Arg335Cys)	rs752399563	-	0.000003979	8	26.2	3.63	-
235	M	TANC2	AD	HT	-	-	MIS	NM_025185.4	c.1364A > G p.(Tyr455Cys)	rs376257499	-	0.00001070	11	25	5.23	-
369	M	TANC2	AD	HT	-	-	MIS	NM_025185.4	c.2978A > G p.(Gln993Arg)	-	-	-	8	26.8	5.78	-
325	M	TRIO	AD	HT	-	-	MIS	NM_007118.4	c.3641C > T p.(Ala1214Val)	rs373893038	-	0.008126	5	25.8	5.93	-
176	M	TRIO	AD	HT	-	-	MIS	NM_007118.4	c.5894G > A p.(Ser1965Asn)	-	-	-	4	23.3	5.48	-

Notes: For variants identified in X-linked genes, based on the X-inactivation analysis, the % of the active mutated allele in carrier female was reported.

Table 4

Mutated genes in the different phenotypic manifestations (ASD, epilepsy, Microcephaly, Macrocephaly, Hypotonia, and Ataxia). Some genes have been found mutated in individuals presenting phenotypic traits that have not been previously associated with these genes (highlighted in bold).
Clinical features	Affected Individuals	Genes carrying Pathogenic/Likely Pathogenic variants
Autistic traits	205	ADNP, ARID1B, ASH1L, CHD8, DEAF1, DYRK1A, FOXP1, GRIN2A, MECP2, PHF21A, PTCHD1, RELN, SATB2, SHANK3, SLC6A1, SYNGAP1, WAC
Epilepsy	84	ANKRD11, CHD8, DYRK1A, EHMT1, GRIN2A, MBD5, MECP2, PHF21A, SLC6A1, SYNGAP1
Microcephaly	45	CHD8, EHMT1, WAC, ANKRD11, MED12, CTNNB1, MECP2, ANKRD11, DYRK1A
Macrocephaly	40	ADNP, FOXP1, GATAD2B, KDM5C, PPP2R5D
Hypotonia	71	ADNP, ANKRD11, ARID1B, CTNNB1, FOXP1, KDM5C, MECP2, SATB2, WAC
Ataxia	30	CHD8, DEAF1, MECP2, SYNGAP1, WAC

The 49 variants of uncertain significance (VUSs) selected for 14% of our cases were found in 32 different genes (Table 3). Further evidence will be required to confirm the association of these variants with the patient’s phenotype (Table 3). During the prioritisation of these variants, significant consideration is given to predictions and conservation scores such as CADD and GERP++, as well as to their frequency in the general population (e.g., gnomAD). Out of these 49 variants, 43 are missense, four are synonymous, one is intronic, and one is a non-frameshift deletion. Among the missense variants, 22 have a CADD score greater than or equal to 25, and 37 variants have a GERP + + score greater than 3 (Table 3). Among the analysed variants, 32 are not found in the population database, and 18 have a significantly low frequency. Familial inheritance has been investigated in 16 cases, while the majority (n = 33) lack segregation analysis; one of the synonymous variants has been confirmed as de novo. Among the inherited variants, except for two heterozygous variants in CNTNAP2 found in trans, the rest are mapped to X-linked genes and are maternally inherited. Most asymptomatic female carriers of X-linked gene variants showed X-inactivation favouring the wild-type allele. The four synonymous variants identified in AP1S2, IQSEC2, MED12, and CNTNAP2, and the deep intronic variant in DEAF1, are predicted to impact splicing mechanisms by Human Splicing Finder (Table 3).

Four VUSs co-occurred with pathogenic variants in four individuals. In detail, the female proband (UniPD_0330) exhibited a heterozygous rare variant p.(Asp35Asn) in EHMT1 in addition to a heterozygous ANKRD11 p.(Lys635GlnfsTer26) pathogenic variant. In this case, the healthy sister did not carry either variant. In addition to the heterozygous frameshift deletion p.(Pro2383GlnfsTer47) in CHD8, the male proband (UniPD_0390), also presented the heterozygous variant in MED13L p.(Ser456Cys). In the UniPD_0170 we found the heterozygous pathogenic frameshift variant p.(Asp826ArgfsTer11) in SYNGAP1 and the hemizygous variant p.(Gly685Ser) in GRIA3. Finally, in UniPD_0388 we detected a novel missense variant in MECP2 in hemizygous state and the heterozygous pathogenic variant p.(Asp8GlufsTer75) in MBD5. In two of these cases, UniPD_0330 and UniPD_0390, parent segregation was not possible due to adoption, resulting in uncertain significance in the interpretation of the missense variants in EHMT1 and MED13L. However, the phenotypes observed in these two cases included clinical features associated with both the pathogenic and the VUS variants. In the other two cases, UniPD_0170 and UniPD_0388, the XCI analysis supports the pathogenicity of the variants in the X-linked genes, MECP2 and GRIA3 (Table 3).

Finally, in 82 patients, we identified variants in 14 genes, such as RELN, KATNAL2, MIB1, associated with autism susceptibility, with low penetrance or with limited information about their involvement in NDDs. These variants were classified by Padua NDD laboratory as Risk Factors (Supplementary Table S2).

Comparison with the CAGI5 dataset

The cohort of individuals selected for the sixth edition of the Critical Assessment of Genome Interpretation (CAGI6) shows clinical characteristics similar to those of the population used in the previous CAGI5 edition (Aspromonte et al., 2019). Among patients with cognitive assessment, a higher distribution of individuals with mild to moderate intellectual disability (ID) is observed—specifically, 31% and 28% respectively—compared to 22% and 25.3% in the CAGI5 cohort (Table 4). In the CAGI6 cohort, a lower percentage of patients had Autism Spectrum Disorder (ASD) or epilepsy, specifically 49% and 20% respectively, compared to 62% and 36.6% in the CAGI5 cohort. On the other hand, patients with macrocephaly are more represented in CAGI6, accounting for 10% compared to 7.3% in CAGI5.

The two cohorts slightly differ in the proportion of pathogenic variants we were able to identify, with 17,3% in CAGI5 and 14.5% in CAGI6; while the number of variants with a likely although not established pathogenic role is higher in the CAGI6 (13%) compared to the previous one (10%).

Genes with higher number of pathogenic variants

In nine genes (ANKRD11, MECP2, ARID1B, CHD8, KDM5C, FOXP1, SYNGAP1, ADNP, SLC6A1) we found more than two pathogenic variants. Importantly, we found multiple individuals with pathogenic/likely pathogenic variants in ASH1L and WAC genes, recently established as definitive NDDs-related genes (Supplementary Table S3) (Leonardi et al., 2020; Liu et al., 2021). Most of the variants we classified as pathogenic were predicted to result in truncated proteins and occurred in genes with strong evidence of dosage sensitivity (ANKRD11, MECP2, ARID1B, FOXP1, SYNGAP1, ADNP, and WAC) (see Supplementary Table S3). Truncating variants is the best-characterised class of variants due to their straightforward mechanism of action and prevalence in children with NDD (Deciphering Developmental Disorders Study, 2017). However, in some of these genes, we also identified pathogenic missense variants.

Although the impact of this class of variants on gene function is more challenging to interpret, resources that collect genetic data from control populations (e.g., gnomAD) and affected individuals (e.g., ClinVar) have been essential for establishing the deleteriousness of these variants. For instance, in patients exhibiting Rett phenotype (UniPD_0118, UniPD_0081), the identified MECP2 missense variants were previously reported as known disease mutations in public databases, allowing us to classify them as pathogenic, even without segregation analysis (Table 2). Additionally, in the case of SLC6A1 missense variant (UniPD_0034), discovering that the known recurrent mutation in an affected individual was also present in the apparently healthy mother prompted us to investigate the family history further, revealing that the mother had experienced episodes of epilepsy during adolescence.

In some genes the identified missense variants were found in protein regions presenting clusters of pathogenic variants. Protein residues near or within clusters of pathogenic variants are more likely to be disease-associated (Pérez-Palma et al., 2020). This evidence, particularly for newly identified variants, can be used as an additional criterion for variant interpretation, as “PM1” category of the ACMG’s guidelines. PM1 is defined as “variants located in a mutational hot spot and/or critical and well-established functional domain without benign variation”. Frequently, the mutation clusters align with structured domains of the protein that are crucial for its primary functions. This is the case of missense variants we identified in the SLC6A1, ARID1B, CHD8, DEAF1, EHMT1, and PPP2R5D genes. For instance, the three variants identified in the SLC6A1 gene alter two functional elements of the γ-Aminobutyric acid (GABA) transporter (GAT1) which are enriched for patient over population variants with high decrease in GABA uptake compared to wild-type (Stefanski et al., 2023). The p.(Trp285Cys) and p.(Gly307Arg) map to the TM6, forming the GABA binding pocket, and the p.(Gly362Arg) is located in the extracellular loop EL4. These findings were useful to confirm the pathogenicity for the newly identified variant p.Trp285Cys that may impact the protein folding disrupting the protein trafficking to the membrane (Motiwala et al., 2022) (Supplementary Fig. S1).

In addition, patient variant clustering can be expected in functionally essential regions along the linear protein sequence. For instance, in the ANKRD11 gene we identified the p.(Arg2536Trp) variant which is situated within a predicted highly charged alpha-helix region where other ANKRD11 pathogenic variants have been observed in individuals with KBG syndrome (OMIM#148050) (Boer et al., 2022) (Supplementary Figure S2). Missense variants of ANKRD11 predominantly cluster in the RD2 repression domain of the protein's C-terminal region (amino acids 2369–2663), often involving arginine residues. These variants have been found to affect ANKRD11 stability and potentially disrupt its proteasome degradation, leading to haploinsufficiency (Boer et al., 2022).

In other cases, the variant clustering is observed in larger regions with unknown functional roles. In these cases, collecting genetic data from different sources is extremely important. For instance, through collaborations with European groups working on NDDs we previously collected and described thirteen families with pathogenic KDM5C variants. This allowed us to observe a clustering of the variants at the C-terminal non-catalytic part of the protein, supporting the existence of distinct KDM5C regulatory functions that utilise enzymatic-independent molecular mechanisms (Leonardi et al., 2023).

In the case of ASH1L gene, we report in this study five missense variants. Although ASH1L variants are generally uncommon, most reported variants are of the truncating type (Stessman et al., 2017). Only a small number of de novo ASH1L missense variants associated with NDDs have been documented, and their functional impacts have not been experimentally investigated. We noticed that three of the detected variants (p.Arg984Cys, p.Asn1060Ser, p.Leu1298Arg), map in the N-terminal segment (aa: 900–1346) between two predicted AT-hook motifs suggesting the functional importance of this region (Table 2 and Table 3) (Supplementary Figure S3). A clustering of the missense variants in the ASH1L N-terminal portion has previously been observed (Liu et al., 2021).

Variants of Uncertain Significance

Even in the selection of variants of uncertain significance, priority was given to factors such as pathogenicity predictions, involvement in functionally relevant regions, and clustering of pathogenic variants. For instance, the p.(Arg303Leu) variant of DEAF1 likely alters the nuclear localization signal (300-YKRRKKE-306) of the protein. This is consistent with functional studies showing that substitutions of Arg302 and Lys304 residues reduces the DEAF1 protein cytoplasmic localization (Huggenvik et al., 1998) (Supplementary Figure S4). Another example is the rare missense variant p.(Ser665Cys), which may affect a phosphorylation site in the Med12-LCEWAV domain. Additionally, the variant p.(Leu992Phe) in IQSEC2 is located in a conserved sequence of the Pleckstrin homology domain (PH domain, 961–1078 aa), where other IQSEC2 pathogenic variants cluster (Supplementary Figure S5) (Shoubridge et al., 2022). Overall, missense variants can have a range of effects on protein sequence and structure, including altering amino acid properties, disrupting protein folding, or affecting the stability of the protein. These changes can interfere with protein function, interaction with other molecules, or its localization within the cell. However, in most of the cases the mechanism underlying disease was found to cause a loss of function, particularly in genes that are highly sensitive to gene dosage. In such cases, even slight reductions in protein activity or expression are expected to lead to significant biological consequences, contributing to disease development. The results obtained from the computational analysis can be a guide for functional tests that may be necessary for an accurate classification of variants of uncertain significance (Sessa et al., 2021).

Unexpected genotype-phenotype correlations

Based on our previous cohort, we found that in some cases with pathogenic variants, the phenotype doesn't fully align with what is expected from the gene alteration. Phenotype consistency is a crucial criterion for establishing variant pathogenicity. However, taken too strictly, this may hinder the inclusion of atypical cases that could expand our understanding of the disease associated with a particular gene and explore new pathogenic mechanisms.

To systematically analyse unexpected genotype-phenotype correlations, we compared patient clinical features with Human Phenotype Ontology (HPO) (Köhler et al., 2021) terms associated with the mutated gene (see Table 4). As in the previous dataset, most unexpected findings were related to abnormal head size. For instance, a patient with macrocrania (UniPD_0129) had a frameshift variant in the ADNP gene, which is associated with various skeletal skull anomalies, including plagiocephaly, trigonocephaly, brachycephaly, and rarely with microcephaly (OMIM 615873). While in the case macrocrania might be an unusual presentation of a skull abnormality, microcephaly was observed in three individuals with pathogenic variants in three different genes - CHD8, WAC, and MED12 - where microcephaly is not typically a feature of the associated disease (Table 4). For instance, the case UniPD_0148 with the pathogenic variant p.(Ser125Ter) in WAC exhibited microcephaly. Abnormal head size has been inconsistently reported in WAC patients, including two cases reported by us and two by Quental and colleagues (Leonardi et al., 2020; Quental et al., 2022). Additionally, a few WAC patients have been reported with macrocephaly (Lugtenberg et al., 2016; Uehara et al., 2018). Although WAC is a relatively new NDD gene, with a growing number of reported cases, we will gain a better understanding of the correlation between alterations in this gene and head size.

Microcephaly has been reported in the UniPD_0210 case where we found the p.(Ala1383Thr) variant of the MED12. Alterations of this gene have been associated with numerous X-linked syndromes, including Lujan-Fryns (OMIM 309520), Opitz-Kaveggia (OMIM 305450), and Ohdo (OMIM 300895). Both Lujan-Fryns and Opitz-Kaveggia are characterised by macrocephaly, while microcephaly has been observed in a few Ohdo Syndrome subtype cases (Langley et al., 2015; Rubin et al., 2020). Interestingly, two of these later cases were siblings carrying the same variant found in our patient (Langley et al., 2015). It has been proposed that different MED12-related disorders may reflect a spectrum of characteristics, rather than distinct syndromes (Langley et al., 2015; Prontera et al., 2016). However, it would be interesting to investigate if different variants of this gene can have different effects on the gene product, and therefore different pathological consequences. This was demonstrated for variants of the TRIO gene, for which the opposite modulation of RAC1 is associated with distinct NDDs characterised by microcephaly (OMIM 617061) or macrocephaly (OMIM 618825) (Barbosa et al., 2020).

Different is the UniPD_0062 case with the truncating p.(Gln392Ter) variant in CHD8, commonly associated with autism and macrocephaly (OMIM 615032). In addition to microcephaly, this individual presents other atypical features for CHD8-related disorders (ataxia, digital anomalies, and behavioural disturbances that are not classifiable as autistic traits). In this case, we can hypothesise that factors other than distinct pathogenic mechanisms resulting from the variant effects may contribute to his phenotypic expression. This could include modifying factors or additional genetic alterations.

This study presents the findings obtained by the application of a 74-gene panel to perform DNA sequencing of 415 individuals with ID and ASD comorbidities. ANKRD11 was found to be the most frequently mutated gene in this cohort, followed by MECP2 and ARID1B. Further individuals have been found carrying de novo variants in ASH1L and WAC genes, for which limited cases have been described in literature. We identified atypical variants, such as a deep intronic variant in the MED13L gene and a mosaic missense variant in the GRIN2A gene. The functional impact and pathogenicity of these variants and others with uncertain significance were investigated based on previous knowledge, in silico evaluation and experimental evidence. Additionally, we discuss unexpected genotype-phenotype correlations observed in the study. In some cases, the phenotypes, in particular anomalies of the head size, did not fully align with the specific altered genes, challenging the establishment of pathogenicity. Of note the relationship between genotype and phenotype can be influenced by various factors, including genetic modifiers, environmental influences, and epigenetic modifications.

Overall, the study provides insights into the genetic landscape of NDDs and the identification of pathogenic variants, highlighting the complexity of genotype-phenotype correlations and the need for further investigation to understand the underlying mechanisms.

Acknowledgements

We are deeply grateful to all patients and their families for their participation. We would like to express our sincere gratitude to Mrs. Marilena Camera for her invaluable technical support throughout the course of this research.

Author Contributions

Conceptualization: EL, MCA; Writing - Original draft preparation: EL, MCA; Writing - Review & Editing: EL, AM, SCET, MCA; Formal analysis: DP, ADC; Experiments and data analysis: EL, MCA, RP; NGS methodological set-up: EL, MCA, RP, EB; EL and MCA designed the computational framework and curated collected data; Supervision: EL, AM, SCET; Clinical data provision: DB, FB, S. Bigoni, S. Boni, CC, SD, ID, EG, IM, DM, SN, MN, FS, LT. All authors revised and approved the final version of the paper.

Funding

The CAGI experiment is supported by the National Institutes of Health (United States) award U24HG007346. S. Bigoni, CC, SD are members of the European Reference Network on Rare Congenital Malformations and Rare Intellectual Disability (ERN-ITHACA ID Agreement: 3HP-HP-FPA ERN-01-2016/739516). This study is partially supported by the European Union—NextGenerationEU through ‘Italiadomani—PNRR’ project CN - G.T.RNA SP. 7 project - National Center for Gene Therapy and Drugs based on RNA Technology (CN3) - [codice MUR CN00000041, C.F. 92315700283]

Data Availability

All data generated or analysed during this study are included in this published article and its Supplementary Information files.

Competing Interests

The authors declare no competing interests.

Ethics approval and consent to participate

This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of University Hospital of Padua, Italy. According to approved protocols of each referring clinical centre, written informed consent was obtained from the probands or their legal representatives for specimen collection and genetic analysis. All individuals recruited provided informed consent for their participation in the study and publication of relevant findings.

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No competing interests reported.

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Supplementary Material The online version contains supplementary material. The supplementary file Online Resource 1 contains Supplementary Figures S1-S5 with legends.
OnlineResource2.xlsx
The Online Resource 2 contains a spreadsheet with two folders relative to Supplementary Table S1 and Supplementary Table S2. In Supplementary Table S1 the presence of ID, ASD, epilepsy, micro- or macrocephaly, hypotonia and ataxia for each patient is indicated as 1 (present), 0 (absent), “.” Information Not provided. Supplementary Table S2 contains the list of the identified variants classified as Risk Factors (RF).

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Genetic Variants and Phenotypic Data Curated for the CAGI6 Intellectual Disability Panel Challenge

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Abstract

Figures

Introduction

Materials and Methods

Patient selection

Gene panel sequencing and data analysis

In silico analysis of the variants

Results

Cohort description

Mutated genes and variants type

Comparison with the CAGI5 dataset

Discussion

Genes with higher number of pathogenic variants

Variants of Uncertain Significance

Unexpected genotype-phenotype correlations

Conclusions

Declarations

Author Contributions

Funding

Data Availability

Competing Interests

Ethics approval and consent to participate

References

Additional Declarations

Supplementary Files

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