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Developmental defects
Original research
ARF1-related disorder: phenotypic and molecular spectrum
  1. Jean-Madeleine de Sainte Agathe1,
  2. Ben Pode-Shakked2,3,
  3. Sophie Naudion4,
  4. Vincent Michaud4,5,
  5. Benoit Arveiler4,5,
  6. Patricia Fergelot4,5,
  7. Jean Delmas6,
  8. Boris Keren1,
  9. Céline Poirsier7,
  10. Fowzan S Alkuraya8,
  11. Brahim Tabarki9,
  12. Eric Bend10,
  13. Kellie Davis11,
  14. Martina Bebin12,
  15. Michelle L Thompson13,
  16. Emily M Bryant14,
  17. Matias Wagner15,16,
  18. Iris Hannibal17,
  19. Jerica Lenberg18,
  20. Martin Krenn19,
  21. Kristen M Wigby20,
  22. Jennifer R Friedman21,22,
  23. Maria Iascone23,
  24. Anna Cereda24,
  25. Térence Miao1,25,
  26. Eric LeGuern1,26,
  27. Emanuela Argilli27,
  28. Elliott Sherr27,
  29. Oana Caluseriu28,
  30. Timothy Tidwell29,
  31. Pinar Bayrak-Toydemir30,
  32. Caroline Hagedorn31,
  33. Melanie Brugger32,
  34. Katharina Vill33,
  35. Francois-Dominique Morneau-Jacob34,
  36. Wendy Chung35,
  37. Kathryn N Weaver2,
  38. Joshua W Owens2,
  39. Ammar Husami2,
  40. Bimal P Chaudhari36,37,38,
  41. Brandon S Stone39,
  42. Katie Burns40,
  43. Rachel Li41,
  44. Iris M de Lange42,
  45. Margaux Biehler43,
  46. Emmanuelle Ginglinger44,
  47. Bénédicte Gérard43,
  48. Rolf W Stottmann2,45,
  49. Aurélien Trimouille4,5,46
  1. 1 Department of Medical Genetics, Groupe Hospitalo-Universitaire Pitié-Salpêtrière, AP-HP.Sorbonne Université, Paris, France
  2. 2 Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
  3. 3 Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
  4. 4 Service de Génétique Médicale, Centre Hospitalier Universitaire de Bordeaux, Bordeaux, France
  5. 5 Maladies Rares : Génétique et Métabolisme (MRGM), U1211, INSERM, Bordeaux, France
  6. 6 Pediatric and Prenatal Imaging Department, Centre Hospitalier Universitaire de Bordeaux Groupe hospitalier Pellegrin, Bordeaux, France
  7. 7 Département de génétique médicale, CHU Reims, Reims, France
  8. 8 Department of Translational Genomic, Center for Genomic Medicine, King Faisal Specialist Hospital & Research Center, Riyadh, Saudi Arabia
  9. 9 Division of Pediatric Neurology, Department of Pediatrics, Prince Sultan Military and Medical City, Riyadh, Saudi Arabia
  10. 10 PreventionGenetics LLC, Marshfield, Wisconsin, USA
  11. 11 Division of Medical Genetics, Royal University Hospital, Saskatoon, Saskatchewan, Canada
  12. 12 UAB Epilepsy Center, The University of Alabama at Birmingham Hospital, Birmingham, Alabama, USA
  13. 13 Greg Cooper’s Laboratory, HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, USA
  14. 14 Gillette Children's Specialty Healthcare, Ann and Robert H Lurie Children's Hospital of Chicago, Chicago, Illinois, USA
  15. 15 Institute of Human Genetics, Technische Universitat Munchen, Munchen, Germany
  16. 16 Institute of Neurogenomics, Helmholtz Zentrum Munchen Deutsches Forschungszentrum fur Umwelt und Gesundheit, Neuherberg, Germany
  17. 17 Department of Pediatrics, University Hospital Munich, Munchen, Germany
  18. 18 Rady Children's Institute for Genomic Medicine, San Diego, California, USA
  19. 19 Department of Neurology, Medizinische Universitat Wien, Wien, Austria
  20. 20 Rady Children’s Hospital-San Diego, University of California, San Diego, California, USA
  21. 21 Department of Neuroscience, Rady Children's Institute for Genomic Medicine, San Diego, California, USA
  22. 22 Division of Neurology, Rady Children's Hospital San Diego, San Diego, California, USA
  23. 23 Laboratorio di Genetica Medica, ASST Papa Giovanni XXIII, Bergamo, Italy
  24. 24 Pediatric Department, ASST Papa Giovanni XXIII, Bergamo, Italy
  25. 25 École d'ingénieurs biotechnologies Paris - SupBiotech, Sup’Biotech, Paris, France
  26. 26 ICM, INSERM, Paris, France
  27. 27 Department of Neurology, University of California San Francisco Division of Hospital Medicine, San Francisco, California, USA
  28. 28 Department of Medical Genetics, University of Alberta Hospital, Edmonton, Alberta, Canada
  29. 29 ARUP Laboratories, Salt Lake City, Utah, USA
  30. 30 Department of Pathology, University of Utah, Salt Lake City, Utah, USA
  31. 31 Division of Medical Genetics, Department of Pediatrics, University of Utah, Salt Lake City, Utah, USA
  32. 32 Institute of Human Genetics, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munchen, Germany
  33. 33 Fachbereich Neuromuskuläre Erkrankungen und klinische Neurophysiologie, Dr. v. Hauner Children’s Hospital, Ludwig-Maximilians-Universität, Munich, Germany
  34. 34 Division of Pediatrics, University of Alberta, Edmonton, Alberta, Canada
  35. 35 Departments of Pediatrics and Medicine, Columbia University, New York City, New York, USA
  36. 36 Divisions of Neonatology, Genetics and Genomic Medicine, Nationwide Children's Hospital, Columbus, Ohio, USA
  37. 37 Department of Pediatrics, The Ohio State University College of Medicine, Columbus, Ohio, USA
  38. 38 Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, Ohio, USA
  39. 39 Divisions of Genetics and Genomic Medicine, Nationwide Children's Hospital, Columbus, Ohio, USA
  40. 40 Sanford Children’s Specialty Clinic, Sioux Falls, South Dakota, USA
  41. 41 Department of Pediatrics, University of South Dakota Sanford School of Medicine, Sioux Falls, South Dakota, USA
  42. 42 Department of Medical Genetics, University Medical Center Utrecht, Utrecht, The Netherlands
  43. 43 Laboratories of Genetic Diagnosis, Institut de Génétique Médicale d'Alsace (IGMA), Strasbourg University Hospitals, Strasbourg, France
  44. 44 Génétique médicale, GHRMSA Hôpital Emile Muller, Mulhouse, France
  45. 45 Department of Pediatrics, University of Cincinnati School of Medicine, Cincinnati, Ohio, USA
  46. 46 Service de Pathologie, University Hospital Centre Bordeaux Pellegrin Hospital Group, Bordeaux, France
  1. Correspondence to Dr Jean-Madeleine de Sainte Agathe, Department of Medical Genetics, Sorbonne University Faculty of Medicine, Paris, 75013, France; jean-madeleine.desainteagathe{at}aphp.fr

Abstract

Purpose ARF1 was previously implicated in periventricular nodular heterotopia (PVNH) in only five individuals and systematic clinical characterisation was not available. The aim of this study is to provide a comprehensive description of the phenotypic and genotypic spectrum of ARF1-related neurodevelopmental disorder.

Methods We collected detailed phenotypes of an international cohort of individuals (n=17) with ARF1 variants assembled through the GeneMatcher platform. Missense variants were structurally modelled, and the impact of several were functionally validated.

Results De novo variants (10 missense, 1 frameshift, 1 splice altering resulting in 9 residues insertion) in ARF1 were identified among 17 unrelated individuals. Detailed phenotypes included intellectual disability (ID), microcephaly, seizures and PVNH. No specific facial characteristics were consistent across all cases, however microretrognathia was common. Various hearing and visual defects were recurrent, and interestingly, some inflammatory features were reported. MRI of the brain frequently showed abnormalities consistent with a neuronal migration disorder.

Conclusion We confirm the role of ARF1 in an autosomal dominant syndrome with a phenotypic spectrum including severe ID, microcephaly, seizures and PVNH due to impaired neuronal migration.

  • epilepsy
  • human genetics
  • sequence analysis, DNA

Data availability statement

Data are available on reasonable request. The variants described in this work are freely available in ClinVar database (VCV000690284.1, SCV002103097 and SCV002104213 to SCV002104223), and in MobiDetails (https://mobidetails.iurc.montp.inserm.fr/MD/vars/ARF1).

http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

https://doi.org/10.1136/jmg-2022-108803

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    WHAT IS ALREADY KNOWN ON THIS TOPIC

    • ARF1-related disorder has been previously described as a syndromic intellectual disability associated with periventricular nodular heterotopia, but with a limited number of cases, most of them are poorly phenotyped.

    WHAT THIS STUDY ADDS

    • This study reports the first detailed phenotyped cohort of 17 individuals with variants in ARF1.

    HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

    • This study implicates ARF1 in a more nuanced phenotype, suggesting a possible relevance for growth parameters or inflammatory manifestations surveillance.

    • This study also recommends the specific use of Mistic predictor (>0.9) to discriminate between pathogenic and benign missense variants.

    Introduction

    Periventricular nodular heterotopia (PVNH) is a neuronal migration disorder consisting of ectopic neuronal nodules along the lateral ventricles. Seizures, microcephaly and intellectual disability (ID) are frequently associated with PVNH.1

    Neuronal migration during human cortical development is dependent on a wide range of interconnected cellular processes such as actin and microtubule cytoskeleton regulation, cell-cell adhesion, apical adhesion, junction formation, vesicle trafficking and membrane protein turnover. Disruption of these processes can lead to periventricular heterotopia where neurons are unable to properly migrate into the developing cortical plate.1 2

    ADP-ribosylation factor proteins (ARF1/3/4/6) are anchored to the membrane via N-terminal myristoylation.3 At the membrane, ARF1 acts as a molecular switch thanks to a transition between two structural conformations: inactive when bound to guanosine diphosphate (GDP), and active when bound to guanosine triphosphate (GTP). ARF1 activation is induced by Guanine Exchange Factors, such as ARFGEF2, which remove the GDP, triggering the GDP to GTP exchange. This causes a conformational change allowing ARF1 to bind different targets, notably through a shift of the loop from Leu39 to Ile49. ARF1GTP promotes trans-Golgi network through the recruitment of clathrin adaptor proteins and the fission step of the vesicle formation. As the vesicle is budding, ARF1 dimerisation is required to continue the coatomer polymerisation, notably when the slimming neck of the bud prohibits ARF1’s further anchorage to the lipid bilayer.4 ARF1-dependent endocytosis has been strongly implicated in PVNH because of its association with genetic alterations of FLNA (MIM: 300049), ARFGEF2 (MIM: 608097) and ARF1 (MIM: 618185) but clinical evidence to date is based on only five cases.5–7

    The aim of this study is to further describe the phenotypic spectrum of ARF1-related disorder as we report a robust cohort of 17 individuals harbouring de novo pathogenic or likely pathogenic variants in ARF1.

    Materials and methods

    Previously unreported individuals harbouring de novo ARF1 variants were recruited using GeneMatcher.8 In addition, two previously reported individuals have been included: the detailed unpublished clinical and radiographic information were collected on an individual previously included in a large cohort of >2200 families with various Mendelian phenotypes and the updated phenotype of one previously published individual has been obtained.6

    Phenotypic and genotypic information was obtained using a standardised questionnaire to evaluate clinical, electroencephalography (EEG) and brain MRI (bMRI) findings as well as genetic variant information. Variants were identified using trio exome sequencing (ES) or genome sequencing (GS) as trio, duo or singleton analyses (table 1). When photos were available, a specific informed consent was obtained from the parents. When available, the bMRI findings were re-evaluated by a single neuroradiologist.

    View this table:
    Table 1

    Clinical characteristics of the cohort

    Variants were interpreted using the American College of Medical Genetics and Genomics/Association for Molecular Pathology guidelines.9 The effects of missense variants were predicted by several in silico tools (table 1, online supplemental figure 1), and mapped to the missense tolerance landscape from MetaDome.10

    Supplemental material

    The pathogenicity of five missense variants was further supported by in vitro functional pulldown assays. We functionally analysed ARF1 activation for four of the patient variants (p.Thr48Ile, p.Phe51Leu, p.Arg99His, p.Lys127Glu) as previously reported for p.Y35H.5 For reproducibility, p.Y35H was also included. Each of the five variants was introduced by site-directed mutagenesis into the ARF1 myc-tagged cDNA (plasmid pCMV6-ARF1-myc, transcript NM_001130408, GenScript, Piscataway, New Jersey, USA), and verified by sequencing prior to transfection (DNA Sequencing and Genotyping Core, CCHMC). Plasmids with reference and mutant sequences were transfected into HEK293T cells in 10 cm2 plates, using the Lipofectamine 3000 Transfection Kit (Invitrogen, Thermo Fisher, Waltham, Massachusetts, USA). HEK293T cells were cultured in Dulbecco’s Modified Eagle’s Medium with 10% fetal bovine serum, 2 mM L-glutamine, Penicillin-Streptomycin per manufacturer’s recommendations. To assess activated ARF1, GST-GGA3 pulldown was performed on cell lysates prior to western blot analysis, using the Active ARF1 Pull-Down and Detection Kit (Thermo Fisher, Waltham, Massachusetts, USA), per manufacturer’s instructions. Processing of samples was performed at 4°C and followed by incubation with GST-GGA3-PBD for 1 hour. For western immunoblotting, anti-ARF1 rabbit monoclonal IgG as primary antibody was diluted at 1:2000 in Intercept buffer prior to incubation at −4°C for 24 hours under agitation. The blot was then incubated with IRDye 800CW Goat antirabbit antibody at 1:15 000 dilution for 1 hour at room temperature under agitation. Western blot analysis results were imaged using Odyssey Sa IFred scanner (LI-COR, Bad Homburg, Germany), equipped with Imaging Studio (Analysis Software V.4.0). Results were quantified using Empiria Studio V.1.3 software. The experiment was performed three times.

    Whole blood was collected on PAXgen tube and total RNA was extracted from patient’s lymphoblastoid cell lines using PAXgene Blood RNA kit (Qiagen). cDNA was generated from 1 μg RNA with the addition of random hexamers and oligo dT primers using the SuperScript II Reverse Transcriptase (ThermoFisher Scientific). Impact on transcription of the c.384+1G>T substitution was then characterised by PCR Sanger sequencing on cDNA according to standard procedures, using primers localised in exons 3 and 5 of ARF1 gene, (F=ACCGTGGAGTACAAGAACATCAGC, R=ACTTCTGGTTCCGGAGCTGAT).

    Structural consequence of missense variants were predicted using SwissModel11 (V.4.1.0), DynaMut212 and visualised with Mol*.13

    Results

    Clinical findings

    The 17 individuals (9 females, 8 males) heterozygous for de novo ARF1 variants ranged in age from 16 months to 14 years (online supplemental table 1). The recurrent substitution c.296G>A; p.(Arg99His) was found in four unrelated individuals, resulting in a total of five different de novo occurrences, including the individual from Ge et al 5 (figure 1, for the detailed clinical description of the cohort, see online supplemental table 1).

    Supplemental material

    Figure 1
    Figure 1

    Clinical overview of 21 individuals with ARF1 variants (17 individuals from this study, 3 individuals previously reported from Ge et al 5 and one from Gana et al.7 Tolerance landscape from MetaDome.10 Plain lines point to the missense location, dashed lines point to non-missense altered residues (either to the premature terminating codon or to the nine residues insertion).

    .

    All individuals with available information presented with varying degrees of ID, ranging from mild to severe. Individuals #2, #7 and #9 (aged 18, 16 and 24 months, respectively) had motor delay along with speech delay, but have not been formally diagnosed with ID.

    Microcephaly below 3 SD was noted in 10 individuals (50%; 10/20), seizures of various types were reported in 8 (50%; 8/16) and PVNH in 3 (20%, 3/15). No correlation was found between seizure history and PVNH. bMRI frequently showed abnormalities: small cerebellum (3/20) and neuronal migration defects including PVNH, cortical dysplasia, polymicrogyria (45%; 9/20) and corpus callosum abnormalities (50%; 10/20) (see online supplemental figure 5).

    Facial characteristics (figure 1) included micrognathia or retrognathia (26%; 5/19), low-set ears (16%; 3/19), dental malposition (10%; 2/19) and short philtrum (10%; 2/19). Of note, individual #4 had obstructive sleep apnoea secondary to her microretrognathia that benefited from mandibular distraction. Visual or hearing impairments were common (58%; 11/19), and included bilateral profound sensorineural hearing loss, cortical vision impairment, strabismus, astigmatism and hyperopia.

    Additional findings included sleep disturbance (32%; 6/19), cardiac defects (16%; 3/19) and hypospadias (2/6 male individuals).

    Interestingly, some idiopathic cutaneous or hepatic manifestations were reported, including hand hyperkeratotic skin (individual #3, individuals from Gana et al), pernio-like rashes involving the hands, feet, upper helices of the ears (individual #9), idiopathic and persistent elevation of liver enzymes (individuals #8 and #9). For individual #9, a liver biopsy was performed at age 1, showing sparse patchy lobular necroinflammatory lesions, no sign of portal inflammation, no haemochromatosis and negative staining for glycogen storage disease.

    Molecular analysis

    Thirteen different de novo variants in ARF1 (NM_001658.4; ENST00000272102.10) were identified in 17 individuals: 10 missense variants, 1 splice variant and 1 frameshift variant. (Nota bene: the missense p.(Phe51Leu) was caused by two different variants, c.153C>A and c.151T>C.) All variants were absent from gnomAD14 (V.2.1.1; V.3.1.2) or deCAF15 and the 10 missense variants were predicted to be deleterious by multiple in silico tools (see ‘Discussion’ section and online supplemental figure 1A). The frameshift variant p.(Asp72Thrfs*17) is predicted to elicit nonsense-mediated decay according to the 50 nucleotides rule,16 and is identified by the Loss-Of-Function Transcript Effect Estimator (V.1.0.314) to result in a loss of function with high confidence.

    The splice variant c.384+1G>T is predicted by SpliceAI17 to create an in-frame donor site, resulting in the inclusion of nine residues near the GTP-binding site (online supplemental figure 1B).

    No other pathogenic or likely pathogenic variant was reported in any of the cases.

    Structural analysis

    The locations of the 10 missense variants in ARF1 are mostly clustered near the GDP-binding domain (figure 1 and figure 2).

    Figure 2
    Figure 2

    (A) Locations of the eight residues (yellow) altered in the two conformations of ARF1. Left, ARF1 in its inactive conformation from 1r8q20; right, ARF1 in active conformation from 6cm936; blue chain: ARF1; grey chain: ARFGEF sec7 domain. Images created using Mol*.13 (B, C) Deleterious effect of patient ARF1 variants on nucleotide activation. Comparison of ARF1 nucleotide activation in lysates of 293 T cells transfected with either the wild-type (WT) ARF1 plasmid or that harbouring one of the five variants (p.Tyr35His, p.Thr48Ile, p.Phe51Leu, p.Arg99His, p.Lys127Glu). Lane 1, basal activated ARF1 in 293 T cells without plasmid transfection. Pulldown for GTP-activated ARF1 in cells transfected with WT (lane 2) vs patient variant-containing ARF1 plasmid (lanes 3–7). ARF1 band is visible at 21 kDa. Western blot analysis results are representative of three independent transfection and pulldown experiments. (C) Quantification of relative nucleotide activation in lysates of 293 T cells transfected with ARF1 plasmids harbouring one of five patient ARF1 variants compared with a WT ARF1 and no plasmid. Mean results are presented as the mean (±SEM) of three separate experiments. P value of the result of each variant in comparison to the WT is presented.

    The Arg19 residue is located at a key position of the GDP-GTP switch. In the inactive conformation (GDP-bound), the Arg19 sidechain points towards an adjacent helix of ARF1 (via Tyr81), however when ARF1 binds GTP, the sidechain of Arg19 is uncovered by the switch, and binds to ARF1 target (adaptor protein AP-1 complex, gamma-1 subunit, Glu41).

    Tyr35 is required for the dimerisation of ARF1 and the Tyr35Ala has been previously shown to prevent in vitro vesicle scission.4

    Thr48 is directly bound to the third phosphate group of GTP. It has been demonstrated to be crucial for the exchange of GDP for GTP during the activation of ARF1.18

    Lys127 is part of the conserved NKXD motif, which binds to the guanine ring of GDP (online supplemental figure 2).19 In ARF1, Lys127 closely interacts with Asp93. Asp93 stabilises the Lys127 sidechain position through a hydrogen bond (online supplemental figure 2).

    The Phe51 residue is located in a switching region of ARF1, which penetrates the hydrophobic groove of guanine exchanging factor. Phe51 is thought to serve as an hydrophobic grip to be ‘pinched off’ by the GEF in order to open the switch region, enabling the GEF to dislodge the GDP from its site (online supplemental figure 3).20

    The recurrent Arg99His variant is predicted to significantly destabilise the region (−1.55 kcal/mol, DynaMut2), with the disruption of one hydrogen-bond stabilising the GDP binding domain (via Asp26, online supplemental figure 2).12

    Pro131 is not located in an established interacting region of ARF1 and is not in direct contact with GDP.

    Functional assay

    The following variants (p.Tyr35His, p.Thr48Ile, p.Phe51Leu, p.Arg99His, p.Lys127Glu, accounting for 11 known individuals) were evaluated by the functional pulldown assay all caused a significant decrease in ARF1 activity (figure 2, p<0.05).

    Discussion

    PVNH has been associated with X linked dominant, autosomal recessive and autosomal dominant syndromes.21–25

    The phenotypic spectrum of ARF1-related disorder includes ID, microcephaly, PVNH and seizures associated with impaired neuronal migration.

    ARF1 is a small GTPase which regulates vesicle trafficking and plays a role in cell adhesion molecule turnover.2 26 Furthermore, ARF1 is implicated in mitochondrial trafficking of endoplasmic reticulum proteins, as well as mitochondrial cholesterol trafficking and fatty acid uptake into the mitochondria.27 ARF1 acts as a molecular switch by alternating between GDP-bound (inactive) and GTP-bound (active) conformations. This activation is performed at the membrane via GDP/GTP exchange by brefeldin A-inhibited guanine nucleotide exchange factor 2 (BIG2, encoded by ARFGEF2). ARF1GTP then can initiate vesicle formation through recruitment of various effectors to the membrane including coat proteins and coat protein adaptors.28 Inhibition of ARF1 has been shown to disrupt neuronal migration, cell-cell adhesion and dendritic Golgi polarisation.26 29

    It is still unclear whether the pathogenicity of ARF1 variants results from a dominant effect or from ARF1 haploinsufficiency.

    Based on gnomAD data, ARF1 is strongly constrained against missense variants.5 14 GeVIR score, a missense intolerance metric,30 ranks ARF1 as the 34th most intolerant gene; GeVIR %: ARF1=17.56 (34/19 361), which is consistent with the missense observed/expected upper bound fraction (MOEUF) from gnomAD; MOEUF: ARF1=0.208 (31/19 704).

    Up to now, the intolerance of ARF1 for truncating variants has been uncertain. ARF1 loss-of-function observed/expected upper bound fraction (LOEUF) metric=0.402 (3595/19 198) is in favour of intolerance, but with limited statistical significance due to the short coding sequence of ARF1. Moreover, a few heterozygous loss-of-function variants have been identified in control individuals: two males (aged >45 yyears and >60 years) carrying a 25 nucleotides deletion resulting in frameshift (rs1010202646) in gnomAD V.2.1.1 (non-neuro), and eight individuals carrying multigenic deletions encompassing ARF1 (nsv523935; nsv516409). For additional information, see online supplemental note 1.

    Based on clinical data, the pathogenicity mechanism of ARF1 variants remains unsolved. First, as suggested by ARFGEF2 biallelic loss-of-function mutations22 31–33 and the clinical overlap of the two syndromes (ID, microcephaly, PVNH, seizures, growth retardation), the defect in neuronal migration is presumed to be caused by reducing the BIG2-ARF1 pathway activity, rather than a gain of function. Furthermore, the two individuals described with truncating variants (one frameshift variant in our cohort and one nonsense variant from Gana et al 7) favour a loss-of-function mechanism through haploinsufficiency, rather than a toxic gain of function. However, this is discordant with the existence of several control individuals with putative loss-of-function variants in ARF1 (rs1010202646; nsv523935; nsv516409). Interestingly, in vitro and in vivo functional assays on ARF1 mutants have shown dominant negative effects. For example, ARF1T31N, a constitutively inactive mutant, has been reported to act as dominant negative when overexpressed.26 The functional assay of Arf1Y35H reduced activation previously reported could not discriminate between a toxic gain of function or a loss of function5 (see online supplemental note 2). Still, to further delineate the exact pathogenicity mechanism, future studies with additional patients will be needed.

    The recurrence of the chr1(GRCh38):g.228097627G>A p.(Arg99His) de novo transition in five individuals suggests a highly mutable position, consistent with the CpG nucleotide context (see online supplemental figure 4).

    We compared the ability of six in silico prediction tools to discriminate pathogenic missense from benign missense variants. Since MISTIC34 showed the best performance (online supplemental figure 1), we recommend its use to apply the prediction criteria (PP3 for variants with MISTIC scores >0.90) during the interpretation of future variants in ARF1.

    Clinical findings confirm the phenotypic spectrum of a neuronal migration disorder, with severe ID, microcephaly and seizures. Unexpectedly, PVNH appeared to be inconsistent (30%), and seizures were poorly correlated with the presence of PVNH, or any other brain malformation. Seizures types were not consistent either: generalised tonic-clonic epilepsy was present in only one individual (#13). bMRI frequently showed abnormalities related to neuronal migration disorders (microcephaly, corpus callosum hypoplasia, polymicrogyria and PVNH), and occasional small cerebellum, which is uncommon in PVNH. Facial characteristics revealed some more common features, like microretrognathia, but were not universal, even between subjects with the same variant. Visual or hearing defects were frequent.

    No major correlation between genotype and phenotype was found. Although of the four verbal individuals (#4, #5, #6, #15), three had alterations of residue Thr48 or Phe51, located in a conserved conformational switch domain.28 This could suggest an association between alterations of this switch-1 region (residues Gly40 to Phe51) and a milder cognitive phenotype, compared with the other alterations.

    Except for the Pro131 residue, all missense variants were located on patently important residues for ARF1 function. We report two different likely pathogenic missense variants on Pro131: one replacing the hydrophobic proline with a positively charged arginine (Pro131Arg), and the other replacing it with another hydrophobic residue (Pro131Leu). This last hydrophobic to hydrophobic change could suggest a proline-specific role of Pro131 in ARF1 function. To our knowledge, Pro131 does not interact with other ARF1 partner. However, proline residues are known to rigidify the peptidic backbone. Pro131 connects the GDP binding loop to the rest of the C-terminal chain. Notably, the precise position and orientation of Asp129 and Lys127 are likely to be crucial for GDP binding. It is possible that Pro131 exerts a favourable constraint to the backbone of this loop, and helps the favourable positioning of GDP binding residues.

    Cutaneous and hepatic manifestations among several individuals are rare and still not significant. However, this could suggest some more systemic roles for ARF1, beyond its implication in cortical neurons development. More patients need to be described to investigate this hypothesis.

    Interestingly, C9orf72, a gene implicated in neuronal degeneration, has recently been reported to act as an effector of ARF1.35 While none of the subjects in this series had evidence of neurodegeneration, the large number of young subjects makes this an important feature to evaluate in the future, as the natural history of this entity becomes better known.

    In summary, we confirm the role of ARF1 as an autosomal dominant ID gene associated with neuronal migration defects. The phenotypic spectrum is characterised by ID, microcephaly, seizures and PVNH.

    Data availability statement

    Data are available on reasonable request. The variants described in this work are freely available in ClinVar database (VCV000690284.1, SCV002103097 and SCV002104213 to SCV002104223), and in MobiDetails (https://mobidetails.iurc.montp.inserm.fr/MD/vars/ARF1).

    Ethics statements

    Patient consent for publication

    Ethics approval

    This study was approved by Comité de Protection des Personnes Sud-Ouest et Outre-Mer III, N°: Avis CEBH 2014/09. Participants gave informed consent to participate in the study before taking part.

    Acknowledgments

    The authors kindly thank all the individuals and their families involved in this study. The authors also thank Dr Lionel Arnaud (AP-HP, Sorbonne Université, Paris, France) for his infographic guidance. EB is an employee of PreventionGenetics.

    References

    1. ↵
      2. Guerrini R ,
      3. Dobyns WB
      . Malformations of cortical development: clinical features and genetic causes. Lancet Neurol 2014;13:710–26. doi:10.1016/S1474-4422(14)70040-7
      OpenUrlCrossRefPubMed
    2. ↵
      2. Lian G ,
      3. Sheen VL
      . Cytoskeletal proteins in cortical development and disease: actin associated proteins in periventricular heterotopia. Front Cell Neurosci 2015;9:99. doi:10.3389/fncel.2015.00099
    3. ↵
      2. Liu Y ,
      3. Kahn RA ,
      4. Prestegard JH
      . Structure and membrane interaction of myristoylated ARF1. Structure 2009;17:79–87. doi:10.1016/j.str.2008.10.020
      OpenUrlCrossRefPubMed
    4. ↵
      2. Beck R ,
      3. Prinz S ,
      4. Diestelkötter-Bachert P , et al
      . Coatomer and dimeric ADP ribosylation factor 1 promote distinct steps in membrane scission. J Cell Biol 2011;194:765–77. doi:10.1083/jcb.201011027
      OpenUrlAbstract/FREE Full Text
    5. ↵
      2. Ge X ,
      3. Gong H ,
      4. Dumas K , et al
      . Missense-depleted regions in population exomes implicate ras superfamily nucleotide-binding protein alteration in patients with brain malformation. Npj Genomic Med 2016;1. doi:10.1038/npjgenmed.2016.36
    6. ↵
      2. Monies D ,
      3. Abouelhoda M ,
      4. Assoum M , et al
      . Lessons learned from large-scale, first-tier clinical exome sequencing in a highly consanguineous population. Am J Hum Genet 2019;105:879. doi:10.1016/j.ajhg.2019.09.019
      OpenUrlCrossRef
    7. ↵
      2. Gana S ,
      3. Casella A ,
      4. Cociglio S , et al
      . ARF1 haploinsufficiency causes periventricular nodular heterotopia with variable clinical expressivity. J Med Genet 2022;59:781–4. doi:10.1136/jmedgenet-2021-107783
      OpenUrlAbstract/FREE Full Text
    8. ↵
      2. Sobreira N ,
      3. Schiettecatte F ,
      4. Valle D , et al
      . GeneMatcher: a matching tool for connecting investigators with an interest in the same gene. Human Mutation 2015;36:928–30. doi:10.1002/humu.22844
      OpenUrlCrossRefPubMed
    9. ↵
      2. Richards S ,
      3. Aziz N ,
      4. Bale S , et al
      . Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American college of medical genetics and genomics and the association for molecular pathology. Genet Med 2015;17:405–24. doi:10.1038/gim.2015.30
      OpenUrlCrossRefPubMed
    10. ↵
      2. Wiel L ,
      3. Baakman C ,
      4. Gilissen D , et al
      . MetaDome: pathogenicity analysis of genetic variants through aggregation of homologous human protein domains. Hum Mutat 2019;40:1030–8. doi:10.1002/humu.23798
      OpenUrlCrossRefPubMed
    11. ↵
      2. Guex N ,
      3. Peitsch MC
      . SWISS-MODEL and the SWISS-pdbviewer: an environment for comparative protein modeling. Electrophoresis 1997;18:2714–23. doi:10.1002/elps.1150181505
      OpenUrlCrossRefPubMedWeb of Science
    12. ↵
      2. Rodrigues CHM ,
      3. Pires DEV ,
      4. Ascher DB
      . DynaMut2: assessing changes in stability and flexibility upon single and multiple point missense mutations. Protein Sci 2021;30:60–9. doi:10.1002/pro.3942
      OpenUrlPubMed
    13. ↵
      2. Sehnal D ,
      3. Bittrich S ,
      4. Deshpande M , et al
      . Mol* viewer: modern web APP for 3D visualization and analysis of large biomolecular structures. Nucleic Acids Res 2021;49:W431–7. doi:10.1093/nar/gkab314
      OpenUrlCrossRefPubMed
    14. ↵
      2. Karczewski KJ ,
      3. Francioli LC ,
      4. Tiao G , et al
      . The mutational constraint spectrum quantified from variation in 141,456 humans. Nature 2020;581:434–43. doi:10.1038/s41586-020-2308-7
      OpenUrlCrossRefPubMed
    15. ↵
      2. Halldorsson BV ,
      3. Eggertsson HP ,
      4. Moore KHS , et al
      . The sequences of 150,119 genomes in the UK biobank. Nature 2022;607:732–40. doi:10.1038/s41586-022-04965-x
      OpenUrlCrossRef
    16. ↵
      2. Nagy E ,
      3. Maquat LE
      . A rule for termination-codon position within intron-containing genes: when nonsense affects RNA abundance. Trends Biochem Sci 1998;23:198–9. doi:10.1016/s0968-0004(98)01208-0
      OpenUrlCrossRefPubMedWeb of Science
    17. ↵
      2. Jaganathan K ,
      3. Kyriazopoulou Panagiotopoulou S ,
      4. McRae JF , et al
      . Predicting splicing from primary sequence with deep learning. Cell 2019;176:535–48. doi:10.1016/j.cell.2018.12.015
      OpenUrlCrossRefPubMed
    18. ↵
      2. Zhou F ,
      3. Dong C ,
      4. Davis JE , et al
      . The mechanism and function of mitogen-activated protein kinase activation by ARF1. Cell Signal 2015;27:2035–44. doi:10.1016/j.cellsig.2015.06.007
      OpenUrlCrossRef
    19. ↵
      2. Liu S ,
      3. Cerione RA ,
      4. Clardy J
      . Structural basis for the guanine nucleotide-binding activity of tissue transglutaminase and its regulation of transamidation activity. Proc Natl Acad Sci USA 2002;99:2743–7. doi:10.1073/pnas.042454899
      OpenUrlAbstract/FREE Full Text
    20. ↵
      2. Renault L ,
      3. Guibert B ,
      4. Cherfils J
      . Structural snapshots of the mechanism and inhibition of a guanine nucleotide exchange factor. Nature 2003;426:525–30. doi:10.1038/nature02197
      OpenUrlCrossRefPubMedWeb of Science
    21. ↵
      2. Parrini E ,
      3. Ramazzotti A ,
      4. Dobyns WB , et al
      . Periventricular heterotopia: phenotypic heterogeneity and correlation with filamin a mutations. Brain 2006;129:1892–906. doi:10.1093/brain/awl125
      OpenUrlCrossRefPubMedWeb of Science
    22. ↵
      2. Sheen VL ,
      3. Ganesh VS ,
      4. Topcu M , et al
      . Mutations in ARFGEF2 implicate vesicle trafficking in neural progenitor proliferation and migration in the human cerebral cortex. Nat Genet 2004;36:69–76. doi:10.1038/ng1276
      OpenUrlCrossRefPubMedWeb of Science
    23. ↵
      2. Cappello S ,
      3. Gray MJ ,
      4. Badouel C , et al
      . Mutations in genes encoding the cadherin receptor-ligand pair DCHS1 and FAT4 disrupt cerebral cortical development. Nat Genet 2013;45:1300–8. doi:10.1038/ng.2765
      OpenUrlCrossRefPubMed
    24. ↵
      2. Broix L ,
      3. Jagline H ,
      4. Ivanova E , et al
      . Mutations in the HECT domain of NEDD4L lead to Akt-mTOR pathway deregulation and cause periventricular nodular heterotopia. Nat Genet 2016;48:1349–58. doi:10.1038/ng.3676
      OpenUrlCrossRefPubMed
    25. ↵
      2. Conti V ,
      3. Carabalona A ,
      4. Pallesi-Pocachard E , et al
      . Periventricular heterotopia in 6q terminal deletion syndrome: role of the c6orf70 gene. Brain 2013;136:3378–94. doi:10.1093/brain/awt249
      OpenUrlCrossRefPubMed
    26. ↵
      2. Zhang J ,
      3. Neal J ,
      4. Lian G , et al
      . Filamin a regulates neuronal migration through brefeldin a-inhibited guanine exchange factor 2-dependent ARF1 activation. J Neurosci 2013;33:15735–46. doi:10.1523/JNEUROSCI.1939-13.2013
      OpenUrlAbstract/FREE Full Text
    27. ↵
      2. Andersen J-P ,
      3. Zhang J ,
      4. Sun H , et al
      . Aster-B coordinates with ARF1 to regulate mitochondrial cholesterol transport. Mol Metab 2020;42:101055. doi:10.1016/j.molmet.2020.101055
      OpenUrl
    28. ↵
      2. Sztul E ,
      3. Chen P-W ,
      4. Casanova JE , et al
      . ARF GTPases and their GEFs and gaps: concepts and challenges. MBoC 2019;30:1249–71. doi:10.1091/mbc.E18-12-0820
      OpenUrl
    29. ↵
      2. Hong E-H ,
      3. Kim J-Y ,
      4. Kim J-H , et al
      . BIG2-ARF1-rhoa-mdia1 signaling regulates dendritic Golgi polarization in hippocampal neurons. Mol Neurobiol 2018;55:7701–16. doi:10.1007/s12035-018-0954-7
      OpenUrl
    30. ↵
      2. Abramovs N ,
      3. Brass A ,
      4. Tassabehji M
      . GeVIR is a continuous gene-level metric that uses variant distribution patterns to prioritize disease candidate genes. Nat Genet 2020;52:35–9. doi:10.1038/s41588-019-0560-2
      OpenUrlCrossRef
    31. ↵
      2. de Wit MCY ,
      3. de Coo IFM ,
      4. Halley DJJ , et al
      . Movement disorder and neuronal migration disorder due to ARFGEF2 mutation. Neurogenetics 2009;10:333–6. doi:10.1007/s10048-009-0192-2
      OpenUrlCrossRefPubMedWeb of Science
    32. ↵
      2. Bardón-Cancho EJ ,
      3. Muñoz-Jiménez L ,
      4. Vázquez-López M , et al
      . Periventricular nodular heterotopia and dystonia due to an ARFGEF2 mutation. Pediatr Neurol 2014;51:461–4. doi:10.1016/j.pediatrneurol.2014.05.008
      OpenUrlCrossRef
    33. ↵
      2. Yilmaz S ,
      3. Gokben S ,
      4. Serdaroglu G , et al
      . The expanding phenotypic spectrum of ARFGEF2 gene mutation: cardiomyopathy and movement disorder. Brain Dev 2016;38:124–7. doi:10.1016/j.braindev.2015.06.004
      OpenUrlCrossRef
    34. ↵
      2. Chennen K ,
      3. Weber T ,
      4. Lornage X , et al
      . MISTIC: a prediction tool to reveal disease-relevant deleterious missense variants. PLOS ONE 2020;15:e0236962. doi:10.1371/journal.pone.0236962
    35. ↵
      2. Su M-Y ,
      3. Fromm SA ,
      4. Zoncu R , et al
      . Structure of the C9orf72 ARF gap complex that is haploinsufficient in ALS and FTD. Nature 2020;585:251–5. doi:10.1038/s41586-020-2633-x
      OpenUrl
    36. ↵
      2. Morris KL ,
      3. Buffalo CZ ,
      4. Stürzel CM , et al
      . HIV-1 nefs are cargo-sensitive AP-1 trimerization switches in tetherin downregulation. Cell 2018;174:659–71. doi:10.1016/j.cell.2018.07.004
      OpenUrlCrossRef

    Supplementary materials

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    Footnotes

    • Twitter @JMdeSteAgathe, @husamia

    • Contributors Conceptualisation: J-MdSA, AT; data curation: J-MdSA, BP-S, SN, VM, BK, CP, FSA, BT, ErB, KD, MartB, MLT, EmB, MW, IH, JL, MK, KMW, JRF, MI, AC, OC, TT, PB-T, MelB, KV, F-DM-J, WC, KW, JWO, AH, BPC, BSS, KB, IMdL, BG, MargB, EG, RL, RWS; formal analysis: J-MdSA, TM, BP-S; writing—original draft: J-MdSA; writing—review ad editing: J-MdSA, BP-S, BA, PF, JD, FSA, ErB, MLT, MW, JL, MK, ÉLG, KV, WC, KW, JWO, AH, BPC, BSS, RWS, AT; guarantor: J-MdSA.

    • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

    • Competing interests None declared.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.