Exome sequencing reveals neurodevelopmental genes in simplex consanguineous Iranian families with syndromic autism.
De novo variants
Consanguineous simplex family
Exome sequencing
Iran
Muscular dystrophy
Neurodevelopmental disorder
Syndromic autism
Journal
BMC medical genomics
ISSN: 1755-8794
Titre abrégé: BMC Med Genomics
Pays: England
ID NLM: 101319628
Informations de publication
Date de publication:
05 Aug 2024
05 Aug 2024
Historique:
received:
16
05
2023
accepted:
23
07
2024
medline:
6
8
2024
pubmed:
6
8
2024
entrez:
5
8
2024
Statut:
epublish
Résumé
Autosomal recessive genetic disorders pose significant health challenges in regions where consanguineous marriages are prevalent. The utilization of exome sequencing as a frequently employed methodology has enabled a clear delineation of diagnostic efficacy and mode of inheritance within multiplex consanguineous families. However, these aspects remain less elucidated within simplex families. In this study involving 12 unrelated simplex Iranian families presenting syndromic autism, we conducted singleton exome sequencing. The identified genetic variants were validated using Sanger sequencing, and for the missense variants in FOXG1 and DMD, 3D protein structure modeling was carried out to substantiate their pathogenicity. To examine the expression patterns of the candidate genes in the fetal brain, adult brain, and muscle, RT-qPCR was employed. In four families, we detected an autosomal dominant gene (FOXG1), an autosomal recessive gene (CHKB), and two X-linked autism genes (IQSEC2 and DMD), indicating diverse inheritance patterns. In the remaining eight families, we were unable to identify any disease-associated genes. As a result, our variant detection rate stood at 33.3% (4/12), surpassing rates reported in similar studies of smaller cohorts. Among the four newly identified coding variants, three are de novo (heterozygous variant p.Trp546Ter in IQSEC2, heterozygous variant p.Ala188Glu in FOXG1, and hemizygous variant p.Leu211Met in DMD), while the homozygous variant p.Glu128Ter in CHKB was inherited from both healthy heterozygous parents. 3D protein structure modeling was carried out for the missense variants in FOXG1 and DMD, which predicted steric hindrance and spatial inhibition, respectively, supporting the pathogenicity of these human mutants. Additionally, the nonsense variant in CHKB is anticipated to influence its dimerization - crucial for choline kinase function - and the nonsense variant in IQSEC2 is predicted to eliminate three functional domains. Consequently, these distinct variants found in four unrelated individuals with autism are likely indicative of loss-of-function mutations. In our two syndromic autism families, we discovered variants in two muscular dystrophy genes, DMD and CHKB. Given that DMD and CHKB are recognized for their participation in the non-cognitive manifestations of muscular dystrophy, it indicates that some genes transcend the boundary of apparently unrelated clinical categories, thereby establishing a novel connection between ASD and muscular dystrophy. Our findings also shed light on the complex inheritance patterns observed in Iranian consanguineous simplex families and emphasize the connection between autism spectrum disorder and muscular dystrophy. This underscores a likely genetic convergence between neurodevelopmental and neuromuscular disorders.
Sections du résumé
BACKGROUND AND OBJECTIVE
OBJECTIVE
Autosomal recessive genetic disorders pose significant health challenges in regions where consanguineous marriages are prevalent. The utilization of exome sequencing as a frequently employed methodology has enabled a clear delineation of diagnostic efficacy and mode of inheritance within multiplex consanguineous families. However, these aspects remain less elucidated within simplex families.
METHODS
METHODS
In this study involving 12 unrelated simplex Iranian families presenting syndromic autism, we conducted singleton exome sequencing. The identified genetic variants were validated using Sanger sequencing, and for the missense variants in FOXG1 and DMD, 3D protein structure modeling was carried out to substantiate their pathogenicity. To examine the expression patterns of the candidate genes in the fetal brain, adult brain, and muscle, RT-qPCR was employed.
RESULTS
RESULTS
In four families, we detected an autosomal dominant gene (FOXG1), an autosomal recessive gene (CHKB), and two X-linked autism genes (IQSEC2 and DMD), indicating diverse inheritance patterns. In the remaining eight families, we were unable to identify any disease-associated genes. As a result, our variant detection rate stood at 33.3% (4/12), surpassing rates reported in similar studies of smaller cohorts. Among the four newly identified coding variants, three are de novo (heterozygous variant p.Trp546Ter in IQSEC2, heterozygous variant p.Ala188Glu in FOXG1, and hemizygous variant p.Leu211Met in DMD), while the homozygous variant p.Glu128Ter in CHKB was inherited from both healthy heterozygous parents. 3D protein structure modeling was carried out for the missense variants in FOXG1 and DMD, which predicted steric hindrance and spatial inhibition, respectively, supporting the pathogenicity of these human mutants. Additionally, the nonsense variant in CHKB is anticipated to influence its dimerization - crucial for choline kinase function - and the nonsense variant in IQSEC2 is predicted to eliminate three functional domains. Consequently, these distinct variants found in four unrelated individuals with autism are likely indicative of loss-of-function mutations.
CONCLUSIONS
CONCLUSIONS
In our two syndromic autism families, we discovered variants in two muscular dystrophy genes, DMD and CHKB. Given that DMD and CHKB are recognized for their participation in the non-cognitive manifestations of muscular dystrophy, it indicates that some genes transcend the boundary of apparently unrelated clinical categories, thereby establishing a novel connection between ASD and muscular dystrophy. Our findings also shed light on the complex inheritance patterns observed in Iranian consanguineous simplex families and emphasize the connection between autism spectrum disorder and muscular dystrophy. This underscores a likely genetic convergence between neurodevelopmental and neuromuscular disorders.
Identifiants
pubmed: 39103847
doi: 10.1186/s12920-024-01969-6
pii: 10.1186/s12920-024-01969-6
doi:
Substances chimiques
Forkhead Transcription Factors
0
Nerve Tissue Proteins
0
FOXG1 protein, human
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
196Subventions
Organisme : Congressionally Directed Medical Research Program
ID : OC220235
Organisme : National Institute of Child Health and Human Development
ID : NICHD 5R01HD033004-15
Organisme : Research Department of the School of Medicine Shahid Beheshti University of Medical Sciences
ID : Pajoohan code: 21827
Informations de copyright
© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.
Références
Association AP. Diagnostic and statistical manual of mental disorders (DSM-5
Lord C, Brugha TS, Charman T, Cusack J, Dumas G, Frazier T, et al. Autism Spectr Disorder. 2020;6(1):1–23.
Fernandez BA, Scherer SWJD. Syndromic autism spectrum disorders: moving from a clinically defined to a molecularly defined approach. 2017;19(4):353.
Ziats CA, Patterson WG, Friez MJPN. Syndromic autism revisited: review of the literature and lessons learned. 2020.
Mossink B, Negwer M, Schubert D, Nadif Kasri N. The emerging role of chromatin remodelers in neurodevelopmental disorders: a developmental perspective. Cell Mol Life Sci. 2021;78(6):2517–63.
doi: 10.1007/s00018-020-03714-5
pubmed: 33263776
Cheon S, Dean M, Chahrour M. The ubiquitin proteasome pathway in neuropsychiatric disorders. Neurobiol Learn Mem. 2019;165:106791.
doi: 10.1016/j.nlm.2018.01.012
pubmed: 29398581
Iossifov I, O’roak BJ, Sanders SJ, Ronemus M, Krumm N, Levy D et al. The contribution of de novo coding mutations to autism spectrum disorder. 2014;515(7526):216–21.
Satterstrom FK, Kosmicki JA, Wang J, Breen MS, De Rubeis S, An J-Y et al. Large-scale exome sequencing study implicates both developmental and functional changes in the neurobiology of autism. 2020;180(3):568–84. e23.
Santos-Cortez RLP, Khan V, Khan FS, Mughal ZU, Chakchouk I, Lee K, et al. Novel candidate genes and variants underlying autosomal recessive neurodevelopmental disorders with intellectual disability. Hum Genet. 2018;137(9):735–52.
doi: 10.1007/s00439-018-1928-6
pubmed: 30167849
pmcid: 6201268
Reuter MS, Tawamie H, Buchert R, Hosny Gebril O, Froukh T, Thiel C, et al. Diagnostic Yield and Novel candidate genes by Exome sequencing in 152 consanguineous families with Neurodevelopmental disorders. JAMA Psychiatry. 2017;74(3):293–9.
doi: 10.1001/jamapsychiatry.2016.3798
pubmed: 28097321
Hiz Kurul S, Oktay Y, Topf A, Szabo NZ, Gungor S, Yaramis A, et al. High diagnostic rate of trio exome sequencing in consanguineous families with neurogenetic diseases. Brain. 2022;145(4):1507–18.
doi: 10.1093/brain/awab395
pubmed: 34791078
Ghasemi MR, Zargari P, Sadeghi H, Bagheri S, Sadeghgi B, Mirfakhraie R et al. Analysis of Cytogenetic Abnormalities in Iranian patients with syndromic autism spectrum disorder: a Case Series. 2022;16(2):117.
Cingolani P, Platts A, Wang LL, Coon M, Nguyen T, Wang L et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. 2012;6(2):80–92.
Li H, Durbin RJB. Fast and accurate long-read alignment with Burrows–Wheeler transform. 2010;26(5):589–95.
Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N et al. The sequence alignment/map format and SAMtools. 2009;25(16):2078–9.
McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, et al. The genome analysis Toolkit: a MapReduce framework for analyzing next-generation. DNA Sequencing data. 2010;20(9):1297–303.
Nature GPCJ. A map of human genome variation from population-scale sequencing. 2010;467(7319):1061.
Fattahi Z, Beheshtian M, Mohseni M, Poustchi H, Sellars E, Nezhadi SH, et al. Iranome: a catalog of genomic variations in the Iranian population. Hum Mutat. 2019;40(11):1968–84.
doi: 10.1002/humu.23880
pubmed: 31343797
Adzhubei IA, Schmidt S, Peshkin L, Ramensky VE, Gerasimova A, Bork P et al. A method and server for predicting damaging missense mutations. 2010;7(4):248–9.
Tt KP, Goel R, Kandasamy K, Keerthikumar S, Kumar S, Mathivanan S, et al. Hum Protein Ref database—2009 Update. 2009;37(suppl1):D767–72.
Kumar P, Henikoff S, Ng PCJN. Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm. 2009;4(7):1073.
Salgado D, Desvignes JP, Rai G, Blanchard A, Miltgen M, Pinard A et al. UMD-predictor: a high‐throughput sequencing compliant system for pathogenicity prediction of any human cDNA substitution. 2016;37(5):439–46.
Schwarz JM, Cooper DN, Schuelke M, Seelow DJN. MutationTaster2: mutation prediction for the deep-sequencing age. 2014;11(4):361–2.
Na SD, Burns TG. Wechsler intelligence scale for children-V: test review. Appl Neuropsychology: Child. 2016;5(2):156–60.
doi: 10.1080/21622965.2015.1015337
DJSAPC W. Wechsler intelligence scale for children–5th Edition (WISC-V). Bloomington, MN: Pearson; 2014.
Kelley LA, Mezulis S, Yates CM, Wass MN. Sternberg MJJNp. The Phyre2 web portal for protein modeling. Prediction Anal. 2015;10(6):845–58.
Waterhouse A, Bertoni M, Bienert S, Studer G, Tauriello G, Gumienny R, et al. SWISS-MODEL: Homology Modelling Protein Struct Complexes. 2018;46(W1):W296–303.
Wiel L, Baakman C, Gilissen D, Veltman JA, Vriend G, Gilissen CJHM, MetaDome. Pathogenicity analysis of genetic variants through aggregation of homologous human protein domains. 2019;40(8):1030–8.
Zhang Z, Xin D, Wang P, Zhou L, Hu L, Kong X et al. Noisy splicing, more than expression regulation, explains why some exons are subject to nonsense-mediated mRNA decay. 2009;7(1):1–13.
Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. 2015;17(5):405–23.
Kircher M, Witten DM, Jain P, O’Roak BJ, Cooper GM. Shendure JJNg. A general framework for estimating the relative pathogenicity of human genetic variants. 2014;46(3):310-5.
Rentzsch P, Witten D, Cooper GM, Shendure J. Kircher MJNar. CADD: predicting the deleteriousness of variants throughout the human genome. 2019;47(D1):D886-D94.
Zhou X, Feliciano P, Shu C, Wang T, Astrovskaya I, Hall JB et al. Integrating de novo and inherited variants in 42,607 autism cases identifies mutations in new moderate-risk genes. 2022;54(9):1305–19.
Alashti SK, Nejabat M, Tabei SMB, Mohammadi S, Fallahi J, Fardaei MJGR. The FOXG1-related syndrome with two novel mutations in the FOXG1 gene. 2020;20:100723.
Iskandar K, Triono A, Sunartini, Dwianingsih EK, Indraswari BW, Kirana IR, et al. Dp71 and intellectual disability in Indonesian patients with Duchenne muscular dystrophy. PLoS ONE. 2022;17(10):e0276640.
doi: 10.1371/journal.pone.0276640
pubmed: 36315559
pmcid: 9621454
Parisi L, Di Filippo T, Glorioso P, La Grutta S, Epifanio MS, Roccella M. Autism spectrum disorders in children affected by Duchenne muscular dystrophy. Minerva Pediatr. 2018;70(3):233–9.
doi: 10.23736/S0026-4946.16.04380-2
pubmed: 29795071
Kutluk G, Kadem N, Bektas O, Eroglu HN. A rare cause of autism spectrum disorder: megaconial muscular dystrophy. Ann Indian Acad Neurol. 2020;23(5):694.
doi: 10.4103/aian.AIAN_98_19
pubmed: 33623274
pmcid: 7887486
Chan SH, Ho RS, Khong P, Chung BH, Tsang MH, Mullin H, et al. Megaconial congenital muscular dystrophy: same novel homozygous mutation in CHKB gene in two unrelated Chinese patients. Neuromuscul Disord. 2020;30(1):47–53.
doi: 10.1016/j.nmd.2019.10.009
pubmed: 31926838
Hu H, Kahrizi K, Musante L, Fattahi Z, Herwig R, Hosseini M, et al. Genet Intellect Disabil Consanguineous Families. 2019;24(7):1027–39.
Thangarajh M, Hendriksen J, McDermott MP, Martens W, Hart KA, Griggs RCJN. Relationships between DMD mutations and neurodevelopment in dystrophinopathy. 2019;93(17):e1597–604.
Hinze S, Jackson MR, Lie S, Jolly L, Field M, Barry S, et al. Incorrect dosage of IQSEC2, a known intellectual disability and epilepsy gene, disrupts dendritic spine morphogenesis. Translational Psychiatry. 2017;7(5):e1110–e.
doi: 10.1038/tp.2017.81
pubmed: 28463240
pmcid: 5534949
Ba R, Yang L, Zhang B, Jiang P, Ding Z, Zhou X, et al. FOXG1 drives transcriptomic networks to specify principal neuron subtypes during the development of the medial pallium. Sci Adv. 2023;9(7):eade2441.
doi: 10.1126/sciadv.ade2441
pubmed: 36791184
pmcid: 9931217
Kreko-Pierce T, Pugh JR. Altered synaptic transmission and excitability of cerebellar nuclear neurons in a mouse model of duchenne muscular dystrophy. Front Cell Neurosci. 2022;16:926518.
doi: 10.3389/fncel.2022.926518
pubmed: 35865113
pmcid: 9294606
Eaton A, Hartley T, Kernohan K, Ito Y, Lamont R, Parboosingh J, et al. When to think outside the autozygome: best practices for exome sequencing in consanguineous families. Clin Genet. 2020;97(6):835–43.
doi: 10.1111/cge.13736
pubmed: 32162313