Next Article in Journal
Expression Changes and Impact of the Extracellular Matrix on Etoposide Resistant Human Retinoblastoma Cell Lines
Previous Article in Journal
Apamin Suppresses LPS-Induced Neuroinflammatory Responses by Regulating SK Channels and TLR4-Mediated Signaling Pathways
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
IJMS
Volume 21
Issue 12
10.3390/ijms21124321
ijms-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Germline Mutation Enrichment in Pathways Controlling Endothelial Cell Homeostasis in Patients with Brain Arteriovenous Malformation: Implication for Molecular Diagnosis

by
Concetta Scimone
1,2,
Francesca Granata
3,
Marcello Longo
3,
Enricomaria Mormina
3,4,
Cristina Turiaco
3,
Antonio A. Caragliano
3,
Luigi Donato
1,2,*,
Antonina Sidoti
1,2,* and
Rosalia D’Angelo
1,2
1
Department of Biomedical, Dental, Morphological and Functional Imaging Sciences, University of Messina, Via Consolare Valeria 1, 98125 Messina, Italy
2
Department of Biomolecular Strategies, Genetics and Avant-Garde Therapies, I.E.ME.S.T., Via Michele Miraglia, 90139 Palermo, Italy
3
Neuroradiology Unit—Department of Biomedical, Dental, Morphological and Functional Imaging Sciences, University of Messina, Via Consolare Valeria 1, 98125 Messina, Italy
4
Department of Clinical and Experimental Medicine, University of Messina, Consolare Valeria 1, 98125 Messina, Italy
*
Authors to whom correspondence should be addressed.
Int. J. Mol. Sci. 2020, 21(12), 4321; https://doi.org/10.3390/ijms21124321
Submission received: 7 May 2020 / Revised: 13 June 2020 / Accepted: 15 June 2020 / Published: 17 June 2020
(This article belongs to the Section Molecular Genetics and Genomics)
Browse Figures
Versions Notes

Abstract

:
Brain arteriovenous malformation (bAVM) is a congenital defect affecting brain microvasculature, characterized by a direct shunt from arterioles to venules. Germline mutations in several genes related to transforming growth factor beta (TGF-β)/BMP signaling are linked to both sporadic and hereditary phenotypes. However, the low incidence of inherited cases makes the genetic bases of the disease unclear. To increase this knowledge, we performed a whole exome sequencing on five patients, on DNA purified by peripheral blood. Variants were filtered based on frequency and functional class. Those selected were validated by Sanger sequencing. Genes carrying selected variants were prioritized to relate these genes with those already known to be linked to bAVM development. Most of the prioritized genes showed a correlation with the TGF-βNotch signaling and vessel morphogenesis. However, two novel pathways related to cilia morphogenesis and ion homeostasis were enriched in mutated genes. These results suggest novel insights on sporadic bAVM onset and confirm its genetic heterogeneity. The high frequency of germline variants in genes related to TGF-β signaling allows us to hypothesize bAVM as a complex trait resulting from the co-existence of low-penetrance loci. Deeper knowledge on bAVM genetics can improve personalized diagnosis and can be helpful with genotype–phenotype correlations.

1. Introduction

Brain arteriovenous malformations (bAVM, OMIM #108010) are vascular malformations affecting brain vasculature. Lack of a capillary bed and a direct shunt from arterioles to venules, as well as pericyte reduction, are characteristics of the lesions [1]. A vessel tangle is formed, usually called nidus. During transition from the feeding arteries to the nidus and then, to the draining veins, vessels show dysregulated differentiation patterns and severe enlargement. From arteries, blood perfuses to the nidus with high pressure, increasing risk of lesion rupture. Moreover, the mix of arterial and venous circulations within these lesions leads to a deficit in cerebral tissue oxygenation. This complex condition usually results in major clinical manifestations such as intracerebral hemorrhage and epileptic seizures, appearing in almost 50% of patients. Disease incidence is about 0.01% worldwide and usually arises at an early age [2]. Nevertheless, it most often occurs as a sporadic condition and only a few dozen cases are reported as inherited with an autosomal dominant pattern. Hereditary bAVM usually coexists with other vascular syndromes, such as Osler-Weber-Rendu syndrome, also known as hereditary hemorrhagic telangiectasia (HHT). HHT includes different phenotypes caused by mutations in genes related to the transforming growth factor beta 2 (TGF-βII) transduction pathway, such as ENG, ACVRL1, SMAD4, and GDF2 [3,4,5]. Due to the severe remodeling rate and recidivism risk after total surgical resection, bAVMs are considered highly dynamic lesions. Therefore, lesion growth is now thought of as the result of continuous endogenous stimuli due to genetic factors. The low frequency of inherited bAVM makes molecular characterization of the disease difficult. Impaired expression of the ephrin family genes and of other vascular differentiation markers was reported by several authors [6,7]. At the same time, the sporadic nature of the disease can also be considered a result of numerous single nucleotide polymorphisms (SNPs) in genes involved in vasculogenesis and early angiogenesis pathways, as, for instance, in vascular endothelial growth factor (VEGF) and Notch signaling [8]. To improve knowledge on bAVM pathogenesis, we purified DNA from peripheral blood and performed a whole exome sequencing (WES) analysis on a group of five patients affected by sporadic bAVM. Then, we clustered genes carrying the detected mutations, highlighting pathways and prioritizing genes mainly linked to bAVM development.

2. Results

2.1. WES, Bioinformatic Analysis, and Filtering

An average of 81,170,229 million reads were output by the runs. Of these, 92.29% showed a Phred quality score > 30. After duplicate discard, an average of 75,411,435 reads were filtered and mapped to the GRCh38 human reference genome. The percentage of on-target reads was on average 71.57%, calculated on the deduplicated mapped read numbers. The quality report summary of each run is provided in Table S1. Regarding variant calling, a mean of 40,090 variants was annotated for each exome. Following the application of the above-mentioned filtering criteria, about 230 variants were selected for each sample. These included non-synonymous, nonsense, and frameshift mutations, whose reported minor allele frequency (MAF) was estimated to be < 0.01. Full lists are available in Table S2.

2.2. Gene Clustering and Prioritization

The ClueGO (Gene Ontology) enrichment analysis allowed to cluster the mutated genes for each exome in order to highlight the pathways they are involved in. In Table 1 only annotated terms showing the Bonferroni-adjusted p-value ≤ 0.05 were reported, both for each single term and for the entire cluster. The full lists are available in Table S3. Annotations related to cell adhesion (GO:1903392, GO:0051895, R-HSA:382054, GO:0038089, GO:0007157, GO:0120193, GO:1904886), cardiovascular development (WP:3668, GO:0003279, GO:0035904, GO:0060840, GO:0060976, GO:0060411), Notch signaling (GO:0007221, R-HSA:9021450, R-HSA:9013508, GO:0045747, WP:268, R-HSA:9012852), and TGFβR signaling (GO:1903846, GO:0030511) were highly represented in all the AVM samples. Furthermore, ontologies related to microtubule assembly and cell motility (GO:0003341, GO:0001578, GO:0001539, GO:0031122, GO:0060285) were also widely frequent. Interestingly, pathways related to ion conductance (GO:1904063, GO:0034766, GO:2001258, GO:0043267, GO:0016248, GO:0008200) were highly enriched in the AVM5 sample.
The table reports annotations from ClueGO enrichment analysis. For each sample, the enriched pathways are mentioned as GO Term (3rd column) and the ontology sources (GeneOntology, WikiPathways, Reactome) are reported (4th column), as well as the clustered genes (7th column). Only annotations showing Bonferroni-adjusted p-value ≤ 0.05 for term or group (5th and 6th columns, respectively) are reported. Full results are available in Table S3. ARFGAP: Adenosine diphosphate Ribosylation Factor-GTPase; AVM: Arteriovenous malformation. The number (1–5) indicates the sample; COPI: coating protein 1; GPCR: G protein-coupled receptor; MAP: Mitogen-Activated Protein; MAPK: Mitogen-Activated Protein Kinase; MKK: MAP Kinase Kinase; NCAM: Neural Cell Adhesion Molecule; PDGF: Platelet Derived Growth Factor; PLXND1: Plexin D1; TAK1: TGF-Beta-Activated Kinase 1; TNF: Tumor Necrosis Factor; IRE1: Inositol-Requiring Protein 1; v-SNARE: Vesicle-Soluble NSF (N-Ethylmaleimide-Sensitive Factor) Attachment Protein Receptor.Gene prioritization aimed to relate selected loci with others, already linked to bAVM development. ToppGene output a full list of the Test Gene Set, ordered according to their overall p-value. For each gene, the overall p-value is calculated on the basis of the single p-value for each training parameter considered. Therefore, also in this case, only genes showing an overall p-value ≤ 0.05 were selected for each sample. Together with this criterion, “Gene Ontology (GO) biological process” annotations were considered as prioritized for the five AVM exomes. These are LTBP4, LTBP1, LRP1, and FBN2 for AVM1; TAB1, RELN, and MAP2K3 for AVM2; KDR and EPHA2 for AVM3; NOTCH3, PLXND1, TAB1, CTBP2, SLIT2, RNF111, MAML1, and CHRNB2 for AVM4; and AXIN1, EPHB2, DVL1, and CAMK2B for AVM5 (Table 2). The complete lists with detailed statistical parameters as well as the annotations linking the prioritized genes to the training genes are available in Table S4.
Although prioritization analysis was quite exhaustive, further loci were considered. These added loci were selected as they are involved in vasculogenesis and carry missense and nonsense variants. In particular, they were FLT4, NCoR2, CCN1, and GIMAP1 in the AVM2 sample; NOTCH4 in AVM3; and ENG and TGFBR2 in AVM5. In particular, ENG and TGFRB2 are known to be highly linked to brain AVM and HHT development. NCoR2 was affected by the novel nonsense variant c.2078G>T (p.Glu693Ter) (Ensembl Transcript ID: ENST00000405201.5). As a consequence, the mutated protein counts 692 amino acids rather than the 2514 amind acids of the wild-type one. The mutation was detected in a heterozygous condition and resulted as “Damaging” and “Disease causing” in SIFT (https://sift.bii.a-star.edu.sg/) [9] and MutationTaster (http://www.mutationtaster.org/) [10] prediction tools, respectively (not shown).

2.3. Sanger Validation

Table 3 lists the variants detected in the genes previously prioritized. All these variants were confirmed by Sanger sequencing and were not detected in our internal 10 control exomes obtained from healthy subjects. Figure 1 reports only the electropherogram of the novel nonsense variant, c.2078G>T (p.Glu693Ter) affecting the NCoR2 locus.

3. Discussion

The genetic landscape of bAVM is to date quite elusive probably due to the very low frequency of inherited cases. Most patients are affected by sporadic forms whose molecular causes are waiting to be clarified. In many cases, lesions are congenital, increasing in size over the years until they become symptomatic. Due to the dynamic nature of bAVM and its high recidivism rate, it is well accepted that lesions arise as a consequence of continuous endogenous stimuli, as inherited and de novo genetic variants or epigenetic modifications occurring during embryo development [11,12]. Therefore, we performed WES analysis on a group of five patients affected by sporadic bAVM, highlighting the main pathways enriched by germline mutated genes. Despite mutated genes differing among patients, the pathways in which they converge are the same. Firstly, we checked for variants in ENG, NOTCH4, and TGFβR2 that are known to be involved in arteriovenous malformation development [13,14]. Then, we searched for KRAS c.35G>T (p.Gly12Val) that was recurrently detected in bAVM patients [15] and none of them carried the mutation, as well as other variants within the gene. However, this was expected as our analysis was performed on DNA purified by peripheral blood. Mosaic-activating KRAS mutations, indeed, were found in sporadic AVM-derived specimens [16,17].
The ClueGO enrichment analysis revealed pathways related to microtubule formation, cell adhesion, and vascular remodeling as being highly enriched (Table 1). Moreover, prioritization analysis was performed for each sample to detect the main genes involved in TGFβR transduction pathways and, therefore, more likely associated to bAVM onset. As reported in Table S4a,b, several loci are noteworthy of consideration and the most relevant are listed in Table 2. However, among prioritized genes, here we briefly discuss those more likely related to bAVM development, in relation to the single sample. This selection was made considering significant p-values related to phenotypes and pathway, outputted by the ToppGene tool (Table S4a).

3.1. AVM1

Regarding AVM1, we focused on LTBP1, LTBP4, FBN2, and LRP1 loci. FBN2, encoding for Fibrillin 2, and LTBP1 and LTBP4 belonging to the “latent transforming growth factor beta binding proteins” family, are ligands of TGF-β receptors [18,19]. With regard to LRP1, encoding for the LDL receptor related protein 1, expression data showed it is expressed in brain endothelial cells where it contributes to chemotactic cell migration, inducing sphingosine-1-phosphate proangiogenic signaling [20]. Moreover, depletion of LRP1 determines defects of both large and small vessel morphogenesis leading to a lethal phenotype [21].

3.2. AVM2

Regarding data obtained from AVM2 exome, we considered variants affecting TAB1, FLT4, RELN, MAP2K3, CCN1, GIMAP1, and NCoR2 loci. TAB1 encodes for the TGF-β activated kinase 1 binding protein 1 and increases endothelial permeability, mediated by the non-canonical TGF-β pathway following inflammation stimuli [22]. Moreover, TAB1 activates the TAK1 kinase, an upstream modulator of the p38 MAPK signaling. MAP2K3 is also involved [23] in the same pathway and, in particular, a physical interaction between TAK1 and MAP2K3 has been reported [24]. Involvement of inflammatory response in bAVM is, to date, well accepted [25,26] and in this context, we detected a nonsense mutation, the c.699G>A (p.Trp233Ter) in GIMAP1 gene. Together with the TGFβR2 signaling, Notch transduction pathways were also reported as promoting AVM development [27]. Therefore, we also considered prioritizing the NCor2 locus, encoding for nuclear receptor co-repressor. We found the novel nonsense mutation, c.2078G>T (p.Glu693Ter) (Figure 1). FLT4, instead, encodes for the vascular endothelial growth factor receptor 3 (VEGFR3) [28]. Finally, we considered CCN1 locus, encoding for the cellular communication network factor 1. Its expression is increased in the extracellular matrix surrounding microvessels and is growth factor-inducible. The protein promotes integrin-mediated endothelial cell adhesion in response to mechanotransduction signaling [29]. This evidence is well congruent with bAVM pathogenesis due to frequent insult by the high blood pressure within the lesions.

3.3. AVM3

Together with NOTCH4, variants carried by EPHA2, EPHB4, and KDR were detected in sample AVM3. EPHA2 and EPHB2 encode for two proteins belonging to the ephrin family, a subgroup of protein-tyrosine kinase receptors. Ephrins are vessel differentiation markers and their role is pivotal during early vasculogenesis. In particular, mesenchymal cells express EPHB2, a feature of arterial morphogenesis. A model proposed by Adams et al. hypothesizes interaction among type-B ephrins differentially expressed in arteries and veins as the basis of a remodeling process that leads to sprouting and capillary network development [30]. EPHB2 expression is upregulated in capillaries during inflammation. This results in increased endothelial permeability and loss of vessel differentiation [31]. The absence of EphA2, instead, was shown to impair the blood–brain barrier, resulting in inhibition of endothelial cell migration and in enhancement of tight junction formation in human brain microvascular endothelial cells (HBMECs) [32]. KDR encodes for the vascular VEGFR2, essential for the organization of the embryonic vasculature and angiogenic sprouting [33].

3.4. AVM4

The highest number of prioritized genes was in the AVM4 sample. GO annotations for biological process revealed involvement in vasculature morphogenesis for NOTCH3, PLXND1, SLIT2, and MAML1 loci. At the embryo stage, VEGF and Notch transduction signaling modulates PLXND1 expression to guide organ vasculogenesis by promoting endothelial cell migration and proliferation [34]. In adults, instead, PLXND1 expression is physiologically low and limited to a few cell types, such as endothelial cells [35]. Balancing effects on migration were reported for SLIT2 [36]. MAML1 is described as a NOTCH coactivator, even if its role in angiogenesis needs more elucidation [37]. Regarding the TGF-β/BMP pathway, we focused on the RNF111 gene, encoding for the E3 ubiquitin-protein ligase. One of its targets is the SMAD7 protein that acts by inhibiting TGF-β/BMP signaling. Therefore, RNF111 activity is required to promote SMAD7 degradation and to enhance the TGF-β/BMP pathway [38]. TGF-β signaling is also upregulated by increased levels of CTBP2 (C-terminal binding protein 2), driving endothelial-to-mesenchymal transition (EMT) [39]. This gene was also mutated in the AVM4 patient. In the end, we focused our attention on the GO terms regarding the response to hypoxia (GO:0001666, GO:0036293, GO:0070482) with the patient as a carrier of rs55685423 (c.1191G>C, p.Gln397His) in the CHRNB2 locus. This gene encodes for the cholinergic receptor nicotinic beta 2 subunit [40]. Its expression was demonstrated in HBMECs, where it contributes to capillary network formation and to angiogenic response to inflammation [41]. Notably, the same ontologies were also found in the AVM3 patient, annotated by the KDR locus.

3.5. AVM5

Finally, in the AVM5 sample we identified two variants in ENG and TGFBR2 loci, rs139398993 (c.392C>T, p.Pro131Leu) and rs35766612 (c.1159G>T, p.Val387Leu), respectively. Moreover, EPHB2 was also affected by a missense variant. Based on human and mouse phenotype ontologies, DVL1 and AXIN1 were annotated to the “cerebrovascular disease” term and, in particular, with AVM and telangiectasia phenotypes. DVL1 is known to control postnatal angiogenesis [42]. AXIN1 encodes for a negative regulator of the Wnt pathway, also enhancing TGF-β signaling by promoting the degradation of the inhibitory SMAD7, in a RNF111-dependent manner [43]. Surprisingly, it was recently described as an important regulator of embryo central nervous system (CNS) angiogenesis, and overexpression leads to premature vascular regression, followed by progressive dilation and inhibition of vascular maturation [44].

3.6. Novel Insights

Together with TGF-β/Notch signaling, GO annotations derived from the ClueGO enrichment analysis (Table 1) highlight a relevant presence of ontologies related to microtubule and cilia organization (GO:0003341, GO:0001578, GO:0031122, GO:0001539, GO:0060285). A recent study demonstrated that cilia are widely represented in endothelial cells during early vasculogenesis and in the later stages as vessel bifurcation point anastomosis. Zebrafish knock-down for cilia biogenesis gene models showed cilia disassembly following shear stress, resulting in remodeling of endothelial cell architecture and increased permeability and hemorrhagic events. Moreover, hemorrhages were only observed in head vasculature and were not observed in the trunk or caudal vessels [45]. Based on this evidence, germline defects in genes controlling cilia assembly might also contribute to brain AVM development as the result of mechanical stress induced by high blood flow and pressure. Clearly, this hypothesis needs to be adequately validated.
Another important property of the blood–brain barrier is the highly selective control of solute transport which is maintained by the exact spatial distribution of membrane transporters and ion channels. Polarization is a key factor for morpho-functional homeostasis of endothelial cells and was shown to be driven by VEGF via Ca2+ specific signaling pathways [46]. Moreover, dysregulation of K+ ion influx in non-excitable cells was shown to lead to hyperpolarization of membrane potential with consequent increased intracellular Ca2+. This results in enhancement of cell proliferation and was also demonstrated in brain capillary endothelial cells [47]. However, if physiological Ca2+ concentration is abnormally excessive, endothelial cells undergo apoptosis [48]. Therefore, we focused attention on GO terms from the ClueGO analysis of sample AVM5. As shown in Table 1, GO terms related to transmembrane ion transport (GO:1904063, GO:0034766, GO:2001258, GO:0043267, GO:0016248, GO:0008200) are largely enriched, as well as those related to membrane biogenesis (GO:0044091, GO:0071709, GO:1904886) making the hypothesis of misregulation in bAVM onset conceivable.
Although these are preliminary findings, they are in accordance with what was recently published by Hauer and colleagues. They describe dysregulated expression of genes also involving cytoskeleton network and transmembrane transport in bAVM-derived specimens, when compared to intracranial control arteries [49]. Therefore, these results allow to elicit other mechanisms in pathogenesis of bAVM not only confined to the canonical TGFβR2 pathway.

3.7. Final Considerations

We discussed loci affected by germline variants in five bAVM samples. Despite these loci differing among the samples, they converged in regulation of the same cellular signaling pathways. This interconnection is represented in Figure 2. The image was obtained by STRING tool Version 11.0 (https://string-db.org/) [50]. Details on nodes and edges are supplied in Table S5.
According to prioritized genes, our data support findings previously reported [51,52] and, in particular, the genetic heterogeneity of the disease. These results suggest that sporadic bAVM is probably not a monogenic condition, rather it arises during early vasculogenesis at the embryo stage. In particular, following fertilization, the combination of both inherited and eventually de novo genetic variants in numerous loci controlling vessel development could result in early vasculogenesis impairment and lesion onset. However, the evidence that these patients develop lesions only in the CNS underlines the importance of the cross-talk between glial cells and endothelium during neurodevelopment and blood–brain barrier morphogenesis. Most genes considered here show an early peculiar expression in neural progenitor cells that contributes to correct vasculogenesis and angiogenetic processes. In this context, proteins related to axon guidance such as Slits, plexins, and ephrins are exhaustive examples [53,54]. However, a last consideration regards genes involved in DNA repair such as WRN, FANCC, BRCA2, TP53BP1, and others carrying rare missense variants. These variants might cause protein functional alteration and, subsequently, DNA repair impairment. At the embryo stage, this might trigger DNA errors resulting in somatic mutations. Clearly, as our study focused on germline variants, the role of somatic mutations is not evaluated here.
Germline genetic variants are endogenous and permanent factors affecting both early vasculogenesis and late angiogenesis. Endothelial remodeling is a continuous phenomenon, and this can explain the increased recidivism rate of bAVM. Therefore, our hypothesis regards the possibility of considering bAVM as the result of the co-existence of numerous low-penetrance loci controlling different processes during endothelial cell differentiation and maturation. This idea is supported by two observations. We selected only loci affected by rare variants (MAF < 0.01) and then, those most likely related to rare disease onset. Rare variants at the same loci were searched for in our internal 10 control exomes obtained from healthy subjects and none was detected.
Clearly, the main limitation of the study is related to the few samples considered and, certainly, results require further validations on a larger patient cohort.
Despite this being a preliminary investigation, the possibility of detecting novel loci and germline mutations potentially involved in bAVM onset will allow to hypothesize a strategy for molecular diagnosis, preferably based on a panel of selected genes.

4. Materials and Methods

4.1. Patient Recruitment and WES Analysis

The study was performed on a group of five Italian patients (AVM1–5) diagnosed with bAVM following cerebral angiography investigation (Figure 3). A severity lesion score was assigned to each patient based on the Spetzler–Martin grading system [55]. Anamnestic data are presented in Table 4. No familiar history of bAVM was reported for the patients and they were classified as sporadic. Patients were fully informed on their enrolment in the study and informed consent was obtained, and for underaged patients as well. DNA samples were collected from peripheral blood and purified by the QIAamp DNA Blood Mini Kit (Qiagen). Qualitative and quantitative measurements of the samples were performed by NanoDrop spectrophotometer (Thermo Fisher Scientific) and by a Qubit fluorometer (Thermo Fisher Scientific). Paired-end libraries were obtained by the SureSelect Human All Exon V7 (Agilent) kit and sequenced on a HiSeq 2500 Illumina platform.

4.2. Bioinformatic Analysis

FastQ data obtained from sequencing runs were quality checked by the FastQC (v.0.11.7) tool (http://www.bioinformatics.babraham.ac.uk/projects/fastqc). Only reads presenting a Phred score ≥ 28 were selected after trimming and aligned to the GRCh38 Human Reference Genome by the Burrows–Wheeler Aligner (BWA) algorithm [56]. Duplicate reads were removed by the MarkDuplicate tool provided by Picard toolkit (v.2.18.23) (“Picard Toolkit.” 2019. Broad Institute, GitHub Repository. http://broadinstitute.github.io/picard/; Broad Institute). Then, the Indel realignment and the base recalibration were performed by the Genome Analysis Toolkit (GATK) (v.4.1.3.0) (https://software.broadinstitute.org/gatk/). Variant calling was executed by FreeBayes [57], while ANNOVAR v.2018Apr16 [58] was used for variant annotation.

4.3. Variant Filtering Criteria

Before proceeding with downstream analysis, annotated genes and variants were filtered on the basis of several criteria. Variants showing quality score < 150 were discarded. This threshold value was established by the observation that several variants with depth lower than 150 were not confirmed by the following Sanger sequencing validation. Filtered variants were classified by functional class and intronic, synonymous, non-coding RNA, and untranslated regions affecting variants were discarded. Missense, nonsense, frameshift, and short indels presenting an MAF < 0.01 were selected. Rare variants were preferred based on the low worldwide incidence of bAVM. For the MAF-based filtering, the values reported in the Genome Aggregation Database (https://gnomad.broadinstitute.org/) [59] and in the 1000 Genomes phase 3 project [60] were considered.

4.4. Gene Clustering and Prioritization

To visualize and functionally group genes carrying filtered variants, the ClueGO plug-in of Cytoscape software was used for each sample [61]. Clustering was performed on the basis of the GO Biological Process, REACTOME and WikiPathways ontologies. Groups showing Bonferroni step down corrected p-value ≤ 0.05 were considered significant and therefore selected for the purpose. Genes within the chosen groups were added to the Test Gene Set in ToppGene (https://toppgene.cchmc.org/) [62], a web-based tool for prioritization of candidate genes based on functional similarity to a training gene list. The Training Gene Set group was made up of ENG, ACVRL1, TGFBR2, SMAD4, and GDF2 genes, already known to be causative of HHT and of a few familiar bAVM cases without HHT. The training parameters selected were “GO:Biological Process”, “Human Phenotype”, “Mouse Phenotype”, “Pathway”, “PubMed”, “Interaction”, and “Disease”. Five different analyses were run, one for each exome data. Statistical parameters were calculated applying the Bonferroni correction, and p-values ≤ 0.05 were considered significant.

4.5. Sanger Validation

Variants carried by prioritized genes were validated by Sanger sequencing, next to polymerase chain reaction (PCR) amplification. Primer sequences and PCR conditions are available upon request. Sanger sequencing was carried out using the BigDyeTerminator© v3.1 Cycle Sequencing Kit chemistry and run on a 3130xl Genetic Analyzer (Applied Biosystems, Thermo Fisher Scientific). Moreover, all variants here considered were further searched in an in-house exome-control dataset obtained by WES data, collected on a cohort of 10 Caucasian healthy subjects, heterogeneous for sex and age. The healthy condition was confirmed by computed tomography.
Patients agreed to be enrolled in the study and their informed consents were obtained. The manuscript does not contain information attributable to their identity. The study involves human participants and was approved by the local Ethics Committee “A.O.U. G. Martino”, N.11/2011 date of approval: 14 December.2011.

5. Conclusions

As knowledge on bAVM is still very elusive, we recruited a group of patients affected by sporadic bAVM and performed WES analysis. Clustering of genes which were affected by rare variants highlighted cytoskeleton impairment as well as defective ion conduction in endothelial cells. Therefore, we hypothesize perturbations at these pathways as possible mechanisms involved in bAVM pathogenesis. We prioritized genes more likely linked to lesion development as FBN2, TAB1, NCoR2, SLIT2, RNF111, CAMK2B, EPHA2, and EPHB2. Although to date no correlation has been reported between gene mutations and clinical phenotype, further characterization of pathways involved in bAVM development could provide a valid criterion to relate molecular features to clinical presentation. In particular, lesion site, bleeding risk, and patient outcome could represent valid prognostic factors linked to patient genotype.

Supplementary Materials

Supplementary materials are available at https://www.mdpi.com/1422-0067/21/12/4321/s1. Table S1: AVM Sample Reports of WES Analysis, Table S2: Selected Variants, Table S3: ClueGO Pathways, Table S4: ToppGene Results. Table S5.: STRING Results.

Author Contributions

Conceptualization, C.S.; methodology, C.S., L.D. and C.T.; investigation: M.L. and F.G.; resources: E.M. and A.A.C.; data curation: L.D.; writing—original draft preparation, C.S.; writing—review and editing, A.S.; supervision, R.D. All authors have read and agreed the final version of the manuscript.

Funding

This research received no external funding.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Winkler, E.A.; Birk, H.; Burkhardt, J.K.; Chen, X.; Yue, J.K.; Guo, D.; Rutledge, W.C.; Lasker, G.F.; Partow, C.; Tihan, T.; et al. Reductions in Brain Pericytes Are Associated With Arteriovenous Malformation Vascular Instability. J. Neurosurg. 2018, 129, 1464–1474. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. Ozpinar, A.; Mendez, G.; Abla, A.A. Epidemiology, genetics, pathophysiology, and prognostic classifications of cerebral arteriovenous malformations. Handb. Clin. Neurol. 2017, 143, 5–13. [Google Scholar] [PubMed]
  3. Zhang, D.; Zhou, F.; Zhao, X.; Bao, B.; Chen, J.; Yang, J. Endoglin is a conserved regulator of vasculogenesis in zebrafish—Implications for hereditary haemorrhagic telangiectasia. Biosci. Rep. 2019, 39. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Crist, A.M.; Lee, A.R.; Patel, N.R.; Westhoff, D.E.; Meadows, S.M. Vascular Deficiency of Smad4 Causes Arteriovenous Malformations: A Mouse Model of Hereditary Hemorrhagic Telangiectasia. Angiogenesis 2018, 21, 363–380. [Google Scholar] [CrossRef] [Green Version]
  5. Wooderchak-Donahue, W.L.; McDonald, J.; O’Fallon, B.; Upton, P.D.; Li, W.; Roman, B.L.; Young, S.; Plant, P.; Fülöp, G.T.; Langa, C.; et al. BMP9 Mutations Cause a Vascular-Anomaly Syndrome With Phenotypic Overlap With Hereditary Hemorrhagic Telangiectasia. Am. J. Hum. Genet. 2013, 93, 530–537. [Google Scholar] [CrossRef] [Green Version]
  6. Sasahara, A.; Kasuya, H.; Akagawa, H.; Ujiie, H.; Kubo, O.; Sasaki, T.; Onda, H.; Sakamoto, Y.; Krischek, B.; Hori, T.; et al. Increased expression of ephrin A1 in brain arteriovenous malformation: DNA microarray analysis. Neurosurg. Rev. 2007, 30, 299–305. [Google Scholar] [CrossRef] [Green Version]
  7. Bai, J.; Wang, Y.J.; Liu, L.; Zhao, Y.L. Ephrin B2 and EphB4 selectively mark arterial and venous vessels in cerebral arteriovenous malformation. J. Int. Med. Res. 2014, 42, 405–415. [Google Scholar] [CrossRef]
  8. Fang, J.; Hirschi, K. Molecular regulation of arteriovenous endothelial cell specification. F1000Research 2019, 8, F1000 Faculty Rev-1208. [Google Scholar] [CrossRef] [Green Version]
  9. Vaser, R.; Adusumalli, S.; Leng, S.N.; Sikic, M.; Ng, P.C. SIFT missense predictions for genomes. Nat. Protoc. 2016, 11, 1–9. [Google Scholar] [CrossRef]
  10. Schwarz, J.M.; Cooper, D.N.; Schuelke, M.; Seelow, D. MutationTaster2: Mutation prediction for the deep-sequencing age. Nat. Methods 2014, 11, 361–362. [Google Scholar] [CrossRef]
  11. Chen, X.; Liu, Y.; Zhou, S.; Nie, S.; Lin, Z.; Zhou, C.; Sun, J.; Gao, X.; Huang, Y. Methylation of the CDKN2A Gene Increases the Risk of Brain Arteriovenous Malformations. J. Mol. Neurosci. 2019, 69, 316–323. [Google Scholar] [CrossRef] [PubMed]
  12. Thomas, J.M.; Surendran, S.; Abraham, M.; Rajavelu, A.; Kartha, C.C. Genetic and epigenetic mechanisms in the development of arteriovenous malformations in the brain. Clin. Epigenetics 2016, 8, 78. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Tual-Chalot, S.; Garcia-Collado, M.; Redgrave, R.E.; Singh, E.; Davison, B.; Park, C.; Lin, H.; Luli, S.; Jin, Y.; Wang, Y.; et al. Loss of Endothelial Endoglin Promotes High-Output Heart Failure Through Peripheral Arteriovenous Shunting Driven by VEGF Signaling. Circ. Res. 2020, 126, 243–257. [Google Scholar] [CrossRef] [PubMed]
  14. Delev, D.; Pavlova, A.; Grote, A.; Boström, A.; Höllig, A.; Schramm, J.; Fimmers, R.; Oldenburg, J.; Simon, M. NOTCH4 gene polymorphisms as potential risk factors for brain arteriovenous malformation development and hemorrhagic presentation. J. Neurosurg. 2017, 126, 1552–1559. [Google Scholar] [CrossRef]
  15. Goss, J.A.; Huang, A.Y.; Smith, E.; Konczyk, D.J.; Smits, P.J.; Sudduth, C.L.; Stapleton, C.; Patel, A.; Alexandrescu, S.; Warman, M.L.; et al. Somatic mutations in intracranial arteriovenous malformations. PLoS ONE 2019, 14, e0226852. [Google Scholar] [CrossRef] [Green Version]
  16. Al-Olabi, L.; Polubothu, S.; Dowsett, K.; Andrews, K.A.; Stadnik, P.; Joseph, A.P.; Knox, R.; Pittman, A.; Clark, G.; Baird, W.; et al. Mosaic RAS/MAPK Variants Cause Sporadic Vascular Malformations Which Respond to Targeted Therapy. J. Clin. Investig. 2018, 128, 1496–1508. [Google Scholar] [CrossRef]
  17. Priemer, D.S.; Vortmeyer, A.O.; Zhang, S.; Chang, H.Y.; Curless, K.L.; Cheng, L. Activating KRAS mutations in arteriovenous malformations of the brain: Frequency and clinicopathologic correlation. Hum. Pathol. 2019, 89, 33–39. [Google Scholar] [CrossRef]
  18. Davis, M.R.; Andersson, R.; Severin, J.; de Hoon, M.; Bertin, N.; Baillie, J.K.; Kawaji, H.; Sandelin, A.; Forrest, A.R.; Summers, K.M. FANTOM Consortium: Transcriptional profiling of the human fibrillin/LTBP gene family, key regulators of mesenchymal cell functions. Mol. Genet. Metab. 2014, 112, 73–83. [Google Scholar] [CrossRef]
  19. Doetschman, T.; Barnett, J.V.; Runyan, R.B.; Camenisch, T.D.; Heimark, R.L.; Granzier, H.L.; Conway, S.J.; Azhar, M. Transforming growth factor beta signaling in adult cardiovascular diseases and repair. Cell Tissue Res. 2012, 347, 203–223. [Google Scholar] [CrossRef] [Green Version]
  20. Vézina, A.; Charfi, C.; Zgheib, A.; Annabi, B. Cerebrovascular Angiogenic Reprogramming upon LRP1 Repression: Impact on Sphingosine-1-Phosphate-Mediated Signaling in Brain Endothelial Cell Chemotactism. Mol. Neurobiol. 2018, 55, 3551–3563. [Google Scholar] [CrossRef]
  21. Nakajima, C.; Haffner, P.; Goerke, S.M.; Zurhove, K.; Adelmann, G.; Frotscher, M.; Herz, J.; Bock, H.H.; May, P. The lipoprotein receptor LRP1 modulates sphingosine-1-phosphate signaling and is essential for vascular development. Development 2014, 141, 4513–4525. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  22. Grimsey, N.J.; Lin, Y.; Narala, R.; Rada, C.C.; Mejia-Pena, H.; Trejo, J. G protein-coupled receptors activate p38 MAPK via a non-canonical TAB1-TAB2- and TAB1-TAB3-dependent pathway in endothelial cells. J. Biol. Chem. 2019, 294, 5867–5878. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  23. Sylvain-Prévost, S.; Ear, T.; Simard, F.A.; Fortin, C.F.; Dubois, C.M.; Flamand, N.; McDonald, P.P. Activation of TAK1 by Chemotactic and Growth Factors, and Its Impact on Human Neutrophil Signaling and Functional Responses. J. Immunol. 2015, 195, 5393–5403. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Di, Y.; Li, S.; Wang, L.; Zhang, Y.; Dorf, M.E. Homeostatic interactions between MEKK3 and TAK1 involved in NF-kappaB signaling. Cell. Signal. 2008, 20, 705–713. [Google Scholar] [CrossRef] [Green Version]
  25. Noshiro, S.; Mikami, T.; Kataoka-Sasaki, Y.; Sasaki, M.; Hashi, K.; Ohtaki, S.; Wanibuchi, M.; Mikuni, N.; Kocsis, J.D.; Honmou, O. Biological relevance of tissue factor and IL-6 in arteriovenous malformations. Neurosurg. Rev. 2017, 40, 359–367. [Google Scholar] [CrossRef]
  26. Shoemaker, L.D.; Fuentes, L.F.; Santiago, S.M.; Allen, B.M.; Cook, D.J.; Steinberg, G.K.; Chang, S.D. Human brain arteriovenous malformations express lymphatic-associated genes. Ann. Clin. Transl. Neurol. 2014, 1, 982–995. [Google Scholar] [CrossRef]
  27. Murphy, P.A.; Kim, T.N.; Huang, L.; Nielsen, C.M.; Lawton, M.T.; Adams, R.H.; Schaffer, C.B.; Wang, R.A. Constitutively active Notch4 receptor elicits brain arteriovenous malformations through enlargement of capillary-like vessels. Proc. Natl. Acad. Sci. USA 2014, 111, 18007–18012. [Google Scholar] [CrossRef] [Green Version]
  28. Hou, Y.; Shin, Y.J.; Han, E.J.; Choi, J.S.; Park, J.M.; Cha, J.H.; Choi, J.Y.; Lee, M.Y. Distribution of vascular endothelial growth factor receptor-3/Flt4 mRNA in adult rat central nervous system. J. Chem. Neuroanat. 2011, 42, 56–64. [Google Scholar] [CrossRef]
  29. Chaqour, B. Caught between a “Rho” and a hard place: Are CCN1/CYR61 and CCN2/CTGF the arbiters of microvascular stiffness? J. Cell Commun. Signal. 2019. [Google Scholar] [CrossRef]
  30. Adams, R.H.; Wilkinson, G.A.; Weiss, C.; Diella, F.; Gale, N.W.; Deutsch, U.; Risau, W.; Klein, R. Roles of ephrinB ligands and EphB receptors in cardiovascular development: Demarcation of arterial/venous domains, vascular morphogenesis, and sprouting angiogenesis. Genes Dev. 1999, 13, 295–306. [Google Scholar] [CrossRef]
  31. Liu, H.; Devraj, K.; Möller, K.; Liebner, S.; Hecker, M.; Korff, T. EphrinB-mediated reverse signalling controls junctional integrity and pro-inflammatory differentiation of endothelial cells. Thromb. Haemost. 2014, 112, 151–163. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  32. Zhou, N.; Zhao, W.D.; Liu, D.X.; Liang, Y.; Fang, W.G.; Li, B.; Chen, Y.H. Inactivation of EphA2 promotes tight junction formation and impairs angiogenesis in brain endothelial cells. Microvasc. Res. 2011, 82, 113–121. [Google Scholar] [CrossRef] [PubMed]
  33. Doronzo, G.; Astanina, E.; Corà, D.; Chiabotto, G.; Comunanza, V.; Noghero, A.; Neri, F.; Puliafito, A.; Primo, L.; Spampanato, C.; et al. TFEB controls vascular development by regulating the proliferation of endothelial cells. EMBO J. 2019, 38, e98250. [Google Scholar] [CrossRef] [PubMed]
  34. Kim, J.; Oh, W.J.; Gaiano, N.; Yoshida, Y.; Gu, C. Semaphorin 3E-Plexin-D1 signaling regulates VEGF function in developmental angiogenesis via a feedback mechanism. Genes Dev. 2011, 25, 1399–1411. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  35. Gu, C.; Yoshida, Y.; Livet, J.; Reimert, D.V.; Mann, F.; Merte, J.; Henderson, C.E.; Jessell, T.M.; Kolodkin, A.L.; Ginty, D.D. Semaphorin 3E and plexin-D1 control vascular pattern independently of neuropilins. Science 2005, 307, 265–268. [Google Scholar] [CrossRef]
  36. Li, G.J.; Yang, Y.; Yang, G.K.; Wan, J.; Cui, D.L.; Ma, Z.H.; Du, L.J.; Zhang, G.M. Slit2 suppresses endothelial cell proliferation and migration by inhibiting the VEGF-Notch signaling pathway. Mol. Med. Rep. 2017, 15, 1981–1988. [Google Scholar] [CrossRef] [Green Version]
  37. Zhang, S.; Kim, J.Y.; Xu, S.; Liu, H.; Yin, M.; Koroleva, M.; Guo, J.; Pei, X.; Jin, Z.G. Endothelial-specific YY1 governs sprouting angiogenesis through directly interacting with RBPJ. Proc. Natl. Acad. Sci. USA 2020, 117, 4792–4801. [Google Scholar] [CrossRef]
  38. Koinuma, D.; Shinozaki, M.; Komuro, A.; Goto, K.; Saitoh, M.; Hanyu, A.; Ebina, M.; Nukiwa, T.; Miyazawa, K.; Imamura, T.; et al. Arkadia amplifies TGF-beta superfamily signalling through degradation of Smad7. EMBO J. 2003, 22, 6458–6470. [Google Scholar] [CrossRef] [Green Version]
  39. Zhou, P.; Wan, X.; Zou, Y.; Chen, Z.; Zhong, A. Transforming growth factor beta (TGF-β) is activated by the CtBP2-p300-AP1 transcriptional complex in chronic renal failure. Int. J. Biol. Sci. 2020, 16, 204–215. [Google Scholar] [CrossRef] [Green Version]
  40. Villa, C.; Colombo, G.; Meneghini, S.; Gotti, C.; Moretti, M.; Ferini-Strambi, L.; Chisci, E.; Giovannoni, R.; Becchetti, A.; Combi, R. CHRNA2 and Nocturnal Frontal Lobe Epilepsy: Identification and Characterization of a Novel Loss of Function Mutation. Front. Mol. Neurosci. 2019, 12, 17. [Google Scholar] [CrossRef] [Green Version]
  41. Heeschen, C.; Weis, M.; Aicher, A.; Dimmeler, S.; Cooke, J.P. A novel angiogenic pathway mediated by non-neuronal nicotinic acetylcholine receptors. J. Clin. Investig. 2002, 110, 527–536. [Google Scholar] [CrossRef]
  42. Peghaire, C.; Bats, M.L.; Sewduth, R.; Jeanningros, S.; Jaspard, B.; Couffinhal, T.; Duplàa, C.; Dufourcq, P. Fzd7 (Frizzled-7) Expressed by Endothelial Cells Controls Blood Vessel Formation Through Wnt/β-Catenin Canonical Signaling. Arterioscler. Thromb. Vasc. Biol. 2016, 36, 2369–2380. [Google Scholar] [CrossRef] [Green Version]
  43. Liu, W.; Rui, H.; Wang, J.; Lin, S.; He, Y.; Chen, M.; Li, Q.; Ye, Z.; Zhang, S.; Chan, S.C.; et al. Axin is a scaffold protein in TGF-beta signaling that promotes degradation of Smad7 by Arkadia. EMBO J. 2006, 25, 1646–1658. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  44. Jensen, L.D.; Hot, B.; Ramsköld, D.; Germano, R.F.V.; Yokota, C.; Giatrellis, S.; Lauschke, V.M.; Hubmacher, D.; Li, M.X.; Hupe, M.; et al. Disruption of the Extracellular Matrix Progressively Impairs Central Nervous System Vascular Maturation Downstream of β-Catenin Signaling. Arterioscler. Thromb. Vasc. Biol. 2019, 39, 1432–1447. [Google Scholar] [CrossRef] [PubMed]
  45. Eisa-Beygi, S.; Benslimane, F.M.; El-Rass, S.; Prabhudesai, S.; Abdelrasoul, M.K.A.; Simpson, P.M.; Yalcin, H.C.; Burrows, P.E.; Ramchandran, R. Characterization of Endothelial Cilia Distribution During Cerebral-Vascular Development in Zebrafish (Danio rerio). Arterioscler. Thromb. Vasc. Biol. 2018, 38, 2806–2818. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  46. Noren, D.P.; Chou, W.H.; Lee, S.H.; Qutub, A.A.; Warmflash, A.; Wagner, D.S.; Popel, A.S.; Levchenko, A. Endothelial cells decode VEGF-mediated Ca2+ signaling patterns to produce distinct functional responses. Sci. Signal. 2016, 9, ra20. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  47. Yamamura, H.; Suzuki, Y.; Yamamura, H.; Asai, K.; Imaizumi, Y. Hypoxic stress up-regulates Kir2.1 expression and facilitates cell proliferation in brain capillary endothelial cells. Biochem. Biophys. Res. Commun. 2016, 476, 386–392. [Google Scholar] [CrossRef] [PubMed]
  48. Yamazaki, D.; Kito, H.; Yamamoto, S.; Ohya, S.; Yamamura, H.; Asai, K.; Imaizumi, Y. Contribution of K(ir)2 potassium channels to ATP-induced cell death in brain capillary endothelial cells and reconstructed HEK293 cell model. Am. J. Physiol. Cell. Physiol. 2011, 300, C75–C86. [Google Scholar] [CrossRef]
  49. Hauer, A.J.; Kleinloog, R.; Giuliani, F.; Rinkel, G.J.E.; de Kort, G.A.; Berkelbach van der Sprenkel, J.W.; van der Zwan, A.; Gosselaar, P.H.; van Rijen, P.C.; de Boer-Bergsma, J.J.; et al. RNA-Sequencing Highlights Inflammation and Impaired Integrity of the Vascular Wall in Brain Arteriovenous Malformations. Stroke 2020, 51, 268–274. [Google Scholar] [CrossRef]
  50. Szklarczyk, D.; Gable, A.L.; Lyon, D.; Junge, A.; Wyder, S.; Huerta-Cepas, J.; Simonovic, M.; Doncheva, N.T.; Morris, J.H.; Bork, P.; et al. STRING v11: Protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 2019, 47, D607–D613. [Google Scholar] [CrossRef] [Green Version]
  51. Wang, K.; Zhao, S.; Liu, B.; Zhang, Q.; Li, Y.; Liu, J.; Shen, Y.; Ding, X.; Lin, J.; Wu, Y.; et al. Perturbations of BMP/TGF-β and VEGF/VEGFR signalling pathways in non-syndromic sporadic brain arteriovenous malformations (BAVM). J. Med. Genet. 2018, 55, 675–684. [Google Scholar] [CrossRef] [PubMed]
  52. Scimone, C.; Donato, L.; Alafaci, C.; Granata, F.; Rinaldi, C.; Longo, M.; D’Angelo, R.; Sidoti, A. High-Throughput Sequencing to Detect Novel Likely Gene-Disrupting Variants in Pathogenesis of Sporadic Brain Arteriovenous Malformations. Front. Genet. 2020, 11, 146. [Google Scholar] [CrossRef] [PubMed]
  53. Guijarro-Muñoz, I.; Cuesta, A.M.; Alvarez-Cienfuegos, A.; Geng, J.G.; Alvarez-Vallina, L.; Sanz, L. The axonal repellent Slit2 inhibits pericyte migration: Potential implications in angiogenesis. Exp. Cell Res. 2012, 318, 371–378. [Google Scholar] [CrossRef]
  54. Harde, E.; Nicholson, L.; Furones Cuadrado, B.; Bissen, D.; Wigge, S.; Urban, S.; Segarra, M.; Ruiz de Almodóvar, C.; Acker-Palmer, A. EphrinB2 regulates VEGFR2 during dendritogenesis and hippocampal circuitry development. Elife 2019, 8, e49819. [Google Scholar] [CrossRef]
  55. Spetzler, R.F.; Martin, N.A. A Proposed Grading System for Arteriovenous Malformations. J. Neurosurg. 1986, 65, 476–483. [Google Scholar] [CrossRef] [PubMed]
  56. Li, H.; Durbin, R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 2009, 25, 1754–1760. [Google Scholar] [CrossRef] [Green Version]
  57. Garrison, E.; Marth, G. Haplotype-based variant detection from short-read sequencing. arXiv 2012, arXiv:1207.3907v2. [Google Scholar]
  58. Wang, K.; Li, M.; Hakonarson, H. ANNOVAR: Functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 2010, 38, e164. [Google Scholar] [CrossRef]
  59. Karczewski, K.J.; Francioli, L.C.; Tiao, G.; Cummings, B.B.; Alföldi, J.; Wang, Q.; Collins, R.L.; Laricchia, K.M.; Ganna, A.; Birnbaum, D.P.; et al. Variation across 141,456 human exomes and genomes reveals the spectrum of loss-of-function intolerance across human protein-coding genes. BioRxiv 2019, 531210. [Google Scholar] [CrossRef] [Green Version]
  60. 1000 Genomes Project Consortium; Auton, A.; Brooks, L.D.; Durbin, R.M.; Garrison, E.P.; Kang, H.M.; Korbel, J.O.; Marchini, J.L.; McCarthy, S.; McVean, G.A.; et al. A global reference for human genetic variation. Nature 2015, 526, 68–74. [Google Scholar]
  61. Bindea, G.; Mlecnik, B.; Hackl, H.; Charoentong, P.; Tosolini, M.; Kirilovsky, A.; Fridman, W.H.; Pagès, F.; Trajanoski, Z.; Galon, J. ClueGO: A cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks. Bioinformatics 2009, 25, 1091–1093. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  62. Chen, J.; Bardes, E.E.; Aronow, B.J.; Jegga, A.G. ToppGene Suite for gene list enrichment analysis and candidate gene prioritization. Nucleic Acids Res. 2009, 37, W305–W311. [Google Scholar] [CrossRef] [PubMed]
Ijms 21 04321 g001 550
Figure 1. The c.2078G>T (p.Glu693Ter) at the NCoR2 locus. Electropherogram shows the novel nonsense mutation affecting the NCor2 gene, detected in heterozygous condition in AVM2 sample. Nucleotide substitution is indicated by the arrow. The brace indicates the DNA sequence corresponding to the triplet carrying the mutated nucleotide (the first one).
Figure 1. The c.2078G>T (p.Glu693Ter) at the NCoR2 locus. Electropherogram shows the novel nonsense mutation affecting the NCor2 gene, detected in heterozygous condition in AVM2 sample. Nucleotide substitution is indicated by the arrow. The brace indicates the DNA sequence corresponding to the triplet carrying the mutated nucleotide (the first one).
Ijms 21 04321 g001
Ijms 21 04321 g002 550
Figure 2. Functional network of prioritized genes. The image describes observed and inferred functional interactions linking prioritized genes. Nodes represent input proteins while edges represent protein–protein associations. Each edge color indicates a specific annotation. Green: activation; red: inhibition; blue: binding; light blue: phenotype; black: reaction; violet: catalysis; pink: posttranslational modification; yellow: transcriptional regulation.
Figure 2. Functional network of prioritized genes. The image describes observed and inferred functional interactions linking prioritized genes. Nodes represent input proteins while edges represent protein–protein associations. Each edge color indicates a specific annotation. Green: activation; red: inhibition; blue: binding; light blue: phenotype; black: reaction; violet: catalysis; pink: posttranslational modification; yellow: transcriptional regulation.
Ijms 21 04321 g002
Ijms 21 04321 g003 550
Figure 3. Imaging for neuroradiological diagnosis. The figure reports cerebral angiographies that confirm the presence of bAVM lesions. The five images refer to the five patients as reported in the text: (A) AVM1, (B) AVM2, (C) AVM3, (D) AVM4, (E) AVM5. AVM lesions are framed in the rectangular box.
Figure 3. Imaging for neuroradiological diagnosis. The figure reports cerebral angiographies that confirm the presence of bAVM lesions. The five images refer to the five patients as reported in the text: (A) AVM1, (B) AVM2, (C) AVM3, (D) AVM4, (E) AVM5. AVM lesions are framed in the rectangular box.
Ijms 21 04321 g003
Table
Table 1. ClueGO (Gene Ontology) enrichment analysis results.
Table 1. ClueGO (Gene Ontology) enrichment analysis results.
SampleGO IDGO TermOntology SourceTerm p-Value Corrected with Bonferroni Step DownGroup p-Value Corrected with Bonferroni Step DownAssociated Genes Found
AVM1GO:0003341cilium movementGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.000.00(ASPM, CFAP206, DNAH1, DNAH5, HYDIN, TEKT5)
GO:0035082axoneme assemblyGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.010.00(CFAP206, DNAH1, DNAH5, HYDIN, RP1L1)
R-HSA:2129379molecules associated with elastic fibersREACTOME_Pathways_27.02.20190.010.05(FBN2, FBN3, LTBP1, LTBP4)
GO:2000105positive regulation of DNA-dependent DNA replicationGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.010.14(CDC7, FLG, SYTL2)
GO:0097722sperm motilityGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.020.00(ASPM, CACNA1I, DNAH1, DNAH5, SLC22A16, TEKT5)
R-HSA:1566948elastic fiber formationREACTOME_Pathways_27.02.20190.020.05(FBN2, FBN3, LTBP1, LTBP4)
GO:0030317flagellated sperm motilityGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.020.00(ASPM, CACNA1I, DNAH1, DNAH5, SLC22A16, TEKT5)
GO:0018410C-terminal protein amino acid modificationGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.030.02(ASPM, LCMT2, SH2B1)
GO:0005044scavenger receptor activityGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.030.03(LRP1, MEGF10, STAB1)
GO:1903078positive regulation of protein localization to plasma membraneGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.030.03(CARD14, LRP1, NKD2)
WP:3668hypothesized pathways in pathogenesis of cardiovascular diseaseWikiPathways_27.02.20190.040.05(FBN2, FBN3, LTBP1)
GO:0001578microtubule bundle formationGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.050.00(CFAP206, DNAH1, DNAH5, HYDIN, RP1L1)
GO:1903392negative regulation of adherens junction organizationGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.050.07(DLEC1, LRP1, TEP1)
GO:0051895negative regulation of focal adhesion assemblyGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.050.07(DLEC1, LRP1, TEP1)
AVM2GO:0031122cytoplasmic microtubule organizationGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.030.02(GOLGA4, KIF19, MBD1, PCM1, TUBGCP6)
GO:0042267natural killer cell mediated cytotoxicityGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.030.08(LGALS9, LILRB1, PIK3R6)
GO:0070228regulation of lymphocyte apoptotic processGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.030.09(IRS2, LGALS9, SLC39A10)
R-HSA:450346activated human TAK1 phosphorylates MKK3/MKK6REACTOME_Reactions_27.02.20190.040.00(MAP2K3, NOD1, TAB1)
GO:0061098positive regulation of protein tyrosine kinase activityGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.050.02(AGXT, DGKQ, DOK7, ERCC6, RELN)
R-HSA:450302activated TAK1 mediates p38 MAPK activationREACTOME_Pathways_27.02.20190.060.00(MAP2K3, NOD1, TAB1)
R-HSA:448424interleukin-17 signalingREACTOME_Pathways_27.02.20190.060.00(MAP2K3, NOD1, TAB1)
R-HSA:382054PDGF binds to extracellular matrix proteinsREACTOME_Reactions_27.02.20190.070.04(COL6A3, COL6A6, SPP1)
WP:231TNF alpha signaling pathwayWikiPathways_27.02.20190.080.00(KSR1, MAP2K3, NFKBIE, NSMAF, TAB1)
R-HSA:186797signaling by PDGFREACTOME_Pathways_27.02.20190.080.04(COL6A3, COL6A6, GRB7, SPP1)
GO:0036498IRE1-mediated unfolded protein responseGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.080.04(ARFGAP3, EXTL1, NR1H4, VAPB, WFS1)
GO:0035176social behaviorGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.090.02(HTT, MBD1, PCM1)
R-HSA:373739ankyrins link voltage-gated sodium and potassium channels to spectrin and L1REACTOME_Reactions_27.02.20190.100.05(ANK2, SCN7A, SPTA1)
R-HSA:445095interaction between L1 and ankyrinsREACTOME_Pathways_27.02.20190.110.05(ANK2, SCN7A, SPTA1)
GO:1901618organic hydroxy compound transmembrane transporter activityGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.110.03(AQP7, HTT, SLC10A6)
GO:0006890retrograde vesicle-mediated transport, Golgi to endoplasmic reticulumGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.130.05(ARFGAP3, CENPE, ERGIC1, HTT, TAPBP)
GO:0035036sperm-egg recognitionGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.130.05(CATSPER2, ZAN, ZP1)
GO:0021846cell proliferation in forebrainGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.130.02(KIF14, MBD1, PCM1)
GO:0018195peptidyl-arginine modificationGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.130.05(NR1H4, PADI2, PRMT7)
GO:0002753cytoplasmic pattern recognition receptor signaling pathwayGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.150.00(ALPK1, DHX58, NOD1, TAB1)
R-HSA:6807875ARFGAP, cargo, v-SNAREs, and p24 proteins bind nascent COPI complexREACTOME_Reactions_27.02.20190.190.05(ANK2, ARFGAP3, SPTA1)
R-HSA:6807877ARFGAPs stimulate ARF GTPase activityREACTOME_Reactions_27.02.20190.190.05(ANK2, ARFGAP3, SPTA1)
R-HSA:450294MAP kinase activationREACTOME_Pathways_27.02.20190.200.00(MAP2K3, NOD1, TAB1)
R-HSA:375165NCAM signaling for neurite out-growthREACTOME_Pathways_27.02.20190.220.04(COL6A3, COL6A6, SPTA1)
R-HSA:2022090assembly of collagen fibrils and other multimeric structuresREACTOME_Pathways_27.02.20190.220.04(COL6A3, COL6A6, LAMA3)
R-HSA:168643nucleotide-binding domain, leucine rich repeat containing receptor (NLR) signaling pathwaysREACTOME_Pathways_27.02.20190.230.00(NOD1, PSTPIP1, TAB1)
GO:1903573negative regulation of response to endoplasmic reticulum stressGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.230.04(NR1H4, PRKN, WFS1)
AVM3GO:0038089positive regulation of cell migration by vascular endothelial growth factor signaling pathwayGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.010.17(KDR, MYO1C, PKD1)
GO:0007157heterophilic cell–cell adhesion via plasma membrane cell adhesion moleculesGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.040.09(HMCN1, RP9, SPG7)
GO:0120193tight junction organizationGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.040.09(EPHA2, MYO1C, PDZD4)
GO:0032688negative regulation of interferon-beta productionGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.040.08(LRRFIP1, MYO1C, NLRC3)
GO:0048739cardiac muscle fiber developmentGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.080.05(MYOM2, OBSL1, SPG7)
AVM4GO:0001539cilium or flagellum-dependent cell motilityGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.000.00(DNAH11, DNAH14, DNAH2, DNAH3, DNAH8, GAS8)
GO:0060285cilium-dependent cell motilityGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.000.00(DNAH11, DNAH14, DNAH2, DNAH3, DNAH8, GAS8)
GO:0007221positive regulation of transcription of Notch receptor targetGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.000.00(MAML1, NOTCH3, OPN1LW, PLXND1, SPHKAP)
WP:334GPCRs, class B secretin-likeWikiPathways_27.02.20190.010.10(ADCYAP1R1, ADGRG2, GLP2R, SCTR)
GO:0003279cardiac septum developmentGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.010.00(CRELD1, DNAH11, LRP2, MAML1, PLXND1, SLIT2, SMO, TAB1)
GO:0071503response to heparinGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.020.01(AOC1, GPIHBP1, SLIT2)
R-HSA:9021450PLXND1 gene expression is stimulated by NOTCH1/NOTCH3 coactivator complexesREACTOME_Reactions_27.02.20190.020.00(MAML1, NOTCH3, PLXND1)
GO:0061476response to anticoagulantGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.030.01(AOC1, GPIHBP1, SLIT2)
R-HSA:2162123synthesis of prostaglandin (PG) and thromboxane (TX)REACTOME_Pathways_27.02.20190.030.19(AKR1C3, HPGD, TBXAS1)
GO:0003205cardiac chamber developmentGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.040.00(CRELD1, DNAH11, LRP2, MAML1, PKD1, PLXND1, SLIT2, SMO, TAB1)
GO:0048278vesicle dockingGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.050.15(CTBP2, SCFD2, STX11)
GO:0007157heterophilic cell–cell adhesion via plasma membrane cell adhesion moleculesGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.050.15(FAT4, HMCN1, NUFIP2)
GO:0021795cerebral cortex cell migrationGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.050.15(SLIT2, SRGAP2, SUN1)
GO:0002753cytoplasmic pattern recognition receptor signaling pathwayGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.050.25(ALPK1, IRAK2, TAB1)
GO:0007616long-term memoryGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.090.04(CTNS, GRIA1, PJA2, PRNP)
GO:0007613memoryGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.110.04(ADGRF1, CHRNB2, CIC, CTNS, GRIA1, PJA2, PRNP)
R-HSA:9013508NOTCH3 intracellular domain regulates transcriptionREACTOME_Pathways_27.02.20190.140.00(MAML1, NOTCH3, PLXND1)
GO:0035904aorta developmentGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.250.00(LRP2, PLXND1, TAB1)
GO:0060840artery developmentGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.250.00(HPGD, LRP2, NOTCH3, PLXND1, TAB1)
GO:0045747positive regulation of Notch signaling pathwayGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.270.00(MAML1, NEPRO, OPN1LW, SPHKAP)
GO:0035082axoneme assemblyGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.330.00(DNAH8, GAS8, RSPH1)
WP:268Notch signalingWikiPathways_27.02.20190.390.00(CTBP2, MAML1, NOTCH3)
GO:1903846positive regulation of cellular response to transforming growth factor beta stimulusGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.400.00(OPN1LW, RNF111, SPHKAP)
GO:0030511positive regulation of transforming growth factor beta receptor signaling pathwayGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.400.00(OPN1LW, RNF111, SPHKAP)
R-HSA:9012852signalling by NOTCH3REACTOME_Pathways_27.02.20190.410.00(MAML1, NOTCH3, PLXND1)
GO:0060976coronary vasculature developmentGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.410.00(LRP2, PLXND1, TAB1)
GO:0060411cardiac septum morphogenesisGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.420.00(DNAH11, LRP2, SLIT2, SMO)
AVM5WP:2572primary focal segmental glomerulosclerosis (FSGS)WikiPathways_27.02.20190.030.05(AGRN, CAMK2B, LAMB2, LMX1B, MKI67)
GO:0006027glycosaminoglycan catabolic processGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.040.08(AGRN, CD44, GPX4)
GO:0031952regulation of protein autophosphorylationGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.080.04(CA5A, CAMK2B, ENG)
GO:1904886beta-catenin destruction complex disassemblyGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.080.05(AXIN1, CA5A, DVL1)
GO:0097150neuronal stem cell population maintenanceGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.090.05(BRCA2, FANCC, MBD1)
R-HSA:2142753arachidonic acid metabolismREACTOME_Pathways_27.02.20190.090.05(CYP4B1, CYP4F3, GPX4, PRXL2B)
GO:1904063negative regulation of cation transmembrane transportGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.100.04(ARHGEF40, CA5A, CAMK2B, EPHB2, KEL)
GO:0007528neuromuscular junction developmentGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.150.05(AGRN, DVL1, LAMB2)
GO:0034766negative regulation of ion transmembrane transportGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.180.04(ARHGEF40, CA5A, CAMK2B, EPHB2, KEL)
GO:0043267negative regulation of potassium ion transportGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.220.04(CA5A, CPAMD8, KEL)
GO:0044091membrane biogenesisGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.250.04(CA5A, EPHB2, PTPRH)
GO:2001258negative regulation of cation channel activityGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.260.04(CA5A, CAMK2B, EPHB2)
GO:0071709membrane assemblyGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.280.04(CA5A, EPHB2, PTPRH)
GO:0016248channel inhibitor activityGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.280.04(CA5A, CAMK2B, PHPT1)
GO:0008200ion channel inhibitor activityGO_BiologicalProcess-EBI-UniProt-GOA_27.02.2019_00h000.280.04(CA5A, CAMK2B, PHPT1)
The table reports annotations from ClueGO enrichment analysis. For each sample, the enriched pathways are mentioned as GO Term (3rd column) and the ontology sources (GeneOntology, WikiPathways, Reactome) are reported (4th column), as well as the clustered genes (7th column). Only annotations showing Bonferroni-adjusted p-value ≤ 0.05 for term or group (5th and 6th columns, respectively) are reported. Full results are available in Table S3. ARFGAP: Adenosine diphosphate Ribosylation Factor-GTPase; AVM: Arteriovenous malformation. The number (1–5) indicates the sample; COPI: coating protein 1; GPCR: G protein-coupled receptor; MAP: Mitogen-Activated Protein; MAPK: Mitogen-Activated Protein Kinase; MKK: MAP Kinase Kinase; NCAM: Neural Cell Adhesion Molecule; PDGF: Platelet Derived Growth Factor; PLXND1: Plexin D1; TAK1: TGF-Beta-Activated Kinase 1; TNF: Tumor Necrosis Factor; IRE1: Inositol-Requiring Protein 1; v-SNARE: Vesicle-Soluble NSF (N-Ethylmaleimide-Sensitive Factor) Attachment Protein Receptor.
Table
Table 2. Genes prioritized by ToppGene tool.
Table 2. Genes prioritized by ToppGene tool.
OntologyFeatureIDNameGenes
GO: Biological ProcessVessel developmentGO:0001525AngiogenesisACVRL1 ENG EPHA2 EPHB2 GDF2 KDR NOTCH3 PLXND1 SLIT2 TGFBR2
GO:0001568Blood vessel developmentACVRL1 ENG EPHA2 EPHB2 GDF2 KDR PKD1 LRP1 LTBP1 TAB1 HPGD LRP2 NOTCH3 PLXND1 SLIT2 SMO TGFBR2
GO:0001569Branching involved in blood vessel morphogenesisENG GDF2 PLXND1 TGFBR2
GO:0001570VasculogenesisENG EPHA2 GDF2 SMO KDR TGFBR2
GO:0001944Vasculature developmentACVRL1 ENG EPHA2 GDF2 KDR PKD1 LRP1 LTBP1 HPGD LRP2 NOTCH3 PLXND1 SLIT2 SMO TAB1 TGFBR2
GO:0048514Blood vessel morphogenesisACVRL1 ENG EPHA2 EPHB2 GDF2 LRP1 KDR HPGD LRP2 NOTCH3 PLXND1 SLIT2 SMO TGFBR2
GO:1901342Regulation of vasculature developmentACVRL1 ENG EPHA2 GDF2 KDR PLXND1 TGFBR2
TGFBR signalingGO:0007179Transforming growth factor beta receptor signaling pathwayACVRL1 AXIN1 ENG FBN2 GDF2 LTBP1 LTBP4 HPGD RNF111 SMAD4 TAB1 TGFBR2
GO:0017015Regulation of transforming growth factor beta receptor signaling pathwayAXIN1 ENG FBN2 GDF2 LTBP1 LTBP4 RNF111 SMAD4 TGFBR2
GO:0071559Response to transforming growth factor betaACVRL1 AXIN1 ENG FBN2 GDF2 HPGD RNF111 LTBP1 LTBP4 SMAD4 TAB1 TGFBR2
GO:0071560Cellular response to transforming growth factor beta stimulusACVRL1 AXIN1 ENG FBN2 GDF2 LTBP1 LTBP4 HPGD RNF111 SMAD4 TAB1 TGFBR2
GO:1903844Regulation of cellular response to transforming growth factor beta stimulusAXIN1 ENG FBN2 GDF2 LTBP1 LTBP4 SMAD4 TGFBR2
Heart developmentGO:0003007Heart morphogenesisACVRL1 DNAH11 ENG SMAD4 FAT4 LRP2 PLXND1 SLIT2 SMAD4 SMO TAB1 TGFBR2
GO:0003205Cardiac chamber developmentDNAH11 ENG LRP2 MAML1 PLXND1 SLIT2 LRP1 LTBP1 SMAD4 SMO TAB1 TGFBR2
GO:0003206Cardiac chamber morphogenesisDNAH11 ENG LRP2 SLIT2 SMAD4 SMO TGFBR2
GO:0003208Cardiac ventricle morphogenesisENG LRP2 SMAD4 TGFBR2
GO:0003231Cardiac ventricle developmentENG LTBP1 LRP2 SLIT2 SMAD4 TGFBR2
GO:0003279Cardiac septum developmentDNAH11 ENG LRP1 LTBP1 LRP2 MAML1 PLXND1 SLIT2 SMAD4 SMO TAB1 TGFBR2
GO:0007507Heart developmentACVRL1 DNAH5 DNAH11 DVL1 ENG KDR PKD1 LRP1 LTBP1 FAT4 LRP2 MAML1 PLXND1 SLIT2 SMAD4 SMO TAB1 TGFBR2
GO:0060411Cardiac septum morphogenesisDNAH11 ENG LRP2 SLIT2 SMAD4 SMO TGFBR2
GO:0072358Cardiovascular system developmentACVRL1 ENG EPHA2 EPHB2 GDF2 KDR PKD1 LRP1 LTBP1 HPGD LRP2 NOTCH3 PLXND1 SLIT2 SMO TAB1 TGFBR2
GO:0072359Circulatory system developmentACVRL1 DNAH5 DNAH11 DVL1 ENG EPHA2 EPHB2 FAT4 GDF2 LRP1 LTBP1 KDR PKD1 HPGD LRP2 MAML1 NOTCH3 PLXND1 SLIT2 SMAD4 SMO TAB1 TGFBR2
GO:2000826Regulation of heart morphogenesisENG SMAD4 SMO TGFBR2
BMP signalingGO:0030509BMP signaling pathwayACVRL1 ENG GDF2 KDR LRP2 SMAD4
GO:0030510Regulation of BMP signaling pathwayACVRL1 ENG GDF2 KDR LRP2 SMAD4
GO:0030513Positive regulation of BMP signaling pathwayACVRL1 ENG GDF2 KDR SMAD4
GO:0071772Response to BMPACVRL1 ENG GDF2 KDR LRP2 SMAD4
GO:0071773Cellular response to BMP stimulusACVRL1 ENG GDF2 KDR LRP2 SMAD4
Endothelial/mesenchymal differentiationGO:0001935Endothelial cell proliferationACVRL1 ENG EPHA2 GDF2 KDR
GO:0001936Regulation of endothelial cell proliferationACVRL1 ENG GDF2 KDR
GO:0003158Endothelium developmentACVRL1 ENG GDF2 KDR SMAD4
GO:0045446Endothelial cell differentiationACVRL1 ENG GDF2 KDR SMAD4
GO:0048762Mesenchymal cell differentiationACVRL1 ENG SMAD4 SMO TGFBR2
GO:0060485Mesenchyme developmentACVRL1 ENG SMAD4 SMO TGFBR2
Hypoxia responseGO:0001666Response to hypoxiaACVRL1 CHRNB2 ENG KDR SMAD4 TGFBR2
GO:0036293Response to decreased oxygen levelsACVRL1 CHRNB2 ENG KDR SMAD4 TGFBR2
GO:0070482Response to oxygen levelsACVRL1 CHRNB2 ENG KDR SMAD4 TGFBR2
Human PhenotypeCerebrovascular malformationsHP:0100026Arteriovenous malformationACVRL1 BRCA2 DVL1 ENG FANCC GDF2 SMAD4
HP:0001009TelangiectasiaACVRL1 BRCA2 ENG FANCC GDF2 SMAD4
HP:0001048Cavernous hemangiomaACVRL1 AXIN1 ENG GDF2 SMAD4
Benign/malignant neoplasmHP:0005306Capillary hemangiomaACVRL1 DVL1 ENG GDF2 KDR SMAD4
HP:0001028HemangiomaACVRL1 AXIN1 DVL1 ENG GDF2 KDR PRKN SMAD4
HP:0100742Vascular neoplasmACVRL1 AXIN1 DVL1 ENG GDF2 KDR PRKN SMAD4
Vessel dilatationHP:0002624Abnormal venous morphologyACVRL1 AXIN1 BRCA2 ENG EPHB2 GDF2 NOTCH3 SMAD4
HP:0002619Varicose veinsACVRL1 AXIN1 ENG GDF2 NOTCH3 SMAD4
HP:0004414Abnormality of the pulmonary arteryACVRL1 ENG FBN2 GDF2 LTBP4 SMAD4 TGFBR2
HP:0004930Abnormality of the pulmonary vasculatureACVRL1 AXIN1 ENG FBN2 GDF2 LTBP4 SMAD4 TGFBR2
HP:0100659Abnormality of the cerebral vasculatureACVRL1 BRCA2 ENG GDF2 NOTCH3 PKD1 PRNP SMAD4 SMO TGFBR2 WFS1
HP:0009145Abnormal cerebral artery morphologyACVRL1 BRCA2 ENG FANCC GDF2 NOTCH3 PKD1 SMAD4 TGFBR2
HP:0011004Abnormal systemic arterial morphologyACVRL1 DNAH11 ENG FBN2 GDF2 NOTCH3 PKD1 SMAD4 TGFBR2
Mouse PhenotypeCerebrovascular malformationsMP:0006093Arteriovenous malformationACVRL1 ENG GDF2 NOTCH3
Vessel dilatationMP:0000259Abnormal vascular developmentACVRL1 CD44 CTBP2 ENG EPHA2 KDR HPGD MAML1 NOTCH3 PLXND1 LTBP1 SMAD4 SMO SPP1 TGFBR2
MP:0001614Abnormal blood vessel morphologyACVRL1 CD44 CTBP2 DNAH11 DNAH5 ENG EPHA2 FBN2 GDF2 KDR PKD1 LMX1B LRP1 LTBP1 LTBP4 HPGD LRP2 MAML1 NOTCH3 PLXND1 SLIT2 NR1H4 SMAD4 SPP1 TAB1 TGFBR2
MP:0003410Abnormal artery developmentACVRL1 ENG NOTCH3 PLXND1 SMO KDR LTBP1 TGFBR2
MP:0004787Abnormal dorsal aorta morphologyACVRL1 ENG KDR TGFBR2
MP:0000267Abnormal heart developmentACVRL1 AXIN1 CTBP2 DNAH5 ENG KDR MAML1 PKD1 SMAD4 SMO TGFBR2
Defects in embryo vasculogenesisMP:0001719Absent vitelline blood vesselsACVRL1 CTBP2 ENG KDR SMO TGFBR2
MP:0003229Abnormal vitelline vasculature morphologyACVRL1 CTBP2 ENG KDR SMO SMAD4 TGFBR2
DiseaseCerebrovascular malformationsC0003857Congenital arteriovenous malformationACVRL1 ENG NOTCH3 SMAD4
Vessel disordersC0334533Arteriovenous hemangiomaACVRL1 ENG NOTCH3 SMAD4
C0007820Cerebrovascular DisordersACVRL1 ENG GDF2 NOTCH3 PKD1 RELN SMAD4 SPP1 TGFBR2
C0042373Vascular DiseasesACVRL1 ENG KDR NOTCH3 PRKN SMAD4 SPP1 TGFBR2
C0002940AneurysmACVRL1 ENG LRP1 LTBP4 PKD1 TGFBR2
The table reports results obtained by ToppGene prioritization analysis giving as Training Gene Set ACVRL1, ENG, GDF2, SMAD4, and TGFBR2. According to the specific ontology, prioritized genes are shown in bold. Results are here summarized and grouped in relation to annotations. Data obtained for the single patient are available in Table S4. BMP: Bone Morphogenetic Protein; TGFBR: Transforming Growth Factor Beta Receptor.
Table
Table 3. Variants affecting prioritized genes.
Table 3. Variants affecting prioritized genes.
LocusGeneHGNC IDSNP IDEnsembl Transcript IDCoding Sequence ChangeEnsembl Protein IDProtein Sequence Change
1p22.3CCN1 *2654rs765069158ENST00000451137 c.G463CENSP00000398736p.Gly155Arg
1p36.12EPHB23393rs142113032ENST00000400191c.847G>CENSP00000383053p.Asp283His
1p36.13EPHA23386rs35484156ENST00000358432c.830C>TENSP00000351209p.Ser277Leu
1p36.33DVL13084rs61735963ENST00000378891c.469G>AENSP00000368169p.Ala157Thr
1q21.3CHRNB21962rs55685423ENST00000368476c.1191G>CENSP00000357461p.Gln397His
2p22.3LTBP16714rs80163321 rs149319598ENST00000404816c. 2248 G>A
c. 2410C>T		ENSP00000386043p.Val750Ile
p.Pro804Ser
3p24.1TGFBR2 *11773rs35766612ENST00000295754c.1159G>TENSP00000295754p.Val387Leu
3q22.1PLXND19107rs137955512ENST00000324093c.2275C>TENSP00000317128p.Pro759Ser
4p15.31SLIT211086rs115629108ENST00000504154c.4049G>AENSP00000422591p.Ser1350Asn
4q12KDR6307rs755067067ENST00000263923c.1990C>TENSP00000263923p.Arg664Cys
5q23.3FBN23604rs28763954ENST00000262464c.976C>TENSP00000262464p.Pro326Ser
5q35.3MAML113632rs113636707ENST00000292599c.569G>AENSP00000292599p.Arg190His
5q35.3FLT4 *3767rs200763913ENST00000261937c.1133G>AENSP00000261937p.Arg378His
6p21.32NOTCH4 *7884rs8192573ENST00000375023c.4037G>AENSP00000364163p.Arg1346Gln
7p13CAMK2B1461rs528355050ENST00000395749c.1577C>TENSP00000379098p.Pro526Leu
7q22.1RELN9957rs114684479 rs79499902ENST00000428762c.3477C>A
c.5284G>A		ENSP00000392423p.Asn1159Lys p.Val1762Ile
7q36.1GIMAP1 *23237rs1326399257ENST00000307194c.699G>AENSP00000302833p.W233X
9q34.11ENG *3349rs139398993ENST00000373203c.392C>TENSP00000362299p.Pro131Leu
10q26.13CTBP22595rs1058301ENST00000334808c.387C>GENSP00000357816p.Asp129Glu
12q13.3LRP16692rs113379328ENST00000243077c.7636G>AENSP00000243077p.Gly2546Ser
12q24.31NCoR2 *7673NovelENST00000405201c..2078G>T ENSP00000384018p.Glu693Ter
15q22.1-q22.2RNF11117384rs142916216ENST00000557998c.888T>GENSP00000452732p.Ile296Met
16p13.3AXIN1903rs200741961ENST00000262320c.644C>TENSP00000262320p.Ser215Leu
17p11.2MAP2K36843rs33911218
rs36047035		ENST00000342679c.118C>G
c.164G>C		ENSP00000345083p.Pro40Ala p.Arg55Thr
19p13.12NOTCH37883rs141320511ENST00000263388c.4552C>AENSP00000263388p.Leu1518Met
19q13.2LTBP46717rs35809725ENST00000308370c.4499A>TENSP00000311905p.Tyr1500Phe
22q13.1TAB118157rs536084162 rs140879164ENST00000216160c.19A>C
c.560G>A		ENSP00000216160p.Ser7Arg p.Arg187His
For each variant, chromosomal band, gene name, HUGO Gene Nomenclature Committee gene name, variant ID, transcript and protein reference IDs of the Ensembl Genome Browser, coding sequence, and amino acid position changes are reported. * Loci not output by the ToppGene tool.
Table
Table 4. Anamnesis data of the patients enrolled in the study.
Table 4. Anamnesis data of the patients enrolled in the study.
PatientSexAge (Years)Age of Onset (Years)SymptomsLesion NumberSpetzler–Martin Grading
AVM1M1412Intracerebral hemorrhage following AVM rupture1—parietal left area2
AVM2M3118Tremor of the left leg, diffuse tremor, seizures1—front-parietal left area (not bleeding)2
AVM3F3229Dizziness, tinnitus, seizures nausea right hemiparesis visus reduction1— parietal left area3
AVM4F8At birthDrowsy status, finalistic limb movement1—proliferative microangiopathy, central left area3
AVM5M75Sudden headache, vertigo, seizures1—anterior-parietal paramedian right area2
The patients are named as mentioned in the text (AVM1–5). Gender, age, and clinical features are reported for each patient. AVM: Arteriovenous malformation. The number (1–5) indicates the sample.

Share and Cite

MDPI and ACS Style

Scimone, C.; Granata, F.; Longo, M.; Mormina, E.; Turiaco, C.; Caragliano, A.A.; Donato, L.; Sidoti, A.; D’Angelo, R. Germline Mutation Enrichment in Pathways Controlling Endothelial Cell Homeostasis in Patients with Brain Arteriovenous Malformation: Implication for Molecular Diagnosis. Int. J. Mol. Sci. 2020, 21, 4321. https://doi.org/10.3390/ijms21124321

AMA Style

Scimone C, Granata F, Longo M, Mormina E, Turiaco C, Caragliano AA, Donato L, Sidoti A, D’Angelo R. Germline Mutation Enrichment in Pathways Controlling Endothelial Cell Homeostasis in Patients with Brain Arteriovenous Malformation: Implication for Molecular Diagnosis. International Journal of Molecular Sciences. 2020; 21(12):4321. https://doi.org/10.3390/ijms21124321

Chicago/Turabian Style

Scimone, Concetta, Francesca Granata, Marcello Longo, Enricomaria Mormina, Cristina Turiaco, Antonio A. Caragliano, Luigi Donato, Antonina Sidoti, and Rosalia D’Angelo. 2020. "Germline Mutation Enrichment in Pathways Controlling Endothelial Cell Homeostasis in Patients with Brain Arteriovenous Malformation: Implication for Molecular Diagnosis" International Journal of Molecular Sciences 21, no. 12: 4321. https://doi.org/10.3390/ijms21124321

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop