Genomic Analysis of <i>SLC9A7 </i>Reveals a Novel Sequence Variant Associated with X-linked Intellectual Disability in a Consanguineous Pashtun Family: Research Article
PDF

Keywords

Neuromics
Pakistan
Pashtuns
Novel
Pathogenic
Mutation

How to Cite

Genomic Analysis of SLC9A7 Reveals a Novel Sequence Variant Associated with X-linked Intellectual Disability in a Consanguineous Pashtun Family: Research Article. (2025). Pak-Euro Journal of Medical and Life Sciences, 8(4), 969-976. https://doi.org/10.31580/4x688964

Abstract

Intellectual disability is characterized by the development of motor, cognitive, language, and social skills. It is a complex condition influenced by either environmental or genetic factors. In this study, we have utilized whole exome sequencing (WES) to identify the genetic causes of Intellectual disability in a consanguineous family from Peshawar, Khyber Pakhtunkhwa, Pakistan. Resultantly, we have identified a novel hemizygous missense variant c.1207T>A (p.S403T) in the SLC9A7 gene on X-chromosome. Consequently, through segregation analysis its X-linked inheritance pattern was validated, with affected members (II-3, II-4, II-5) exhibiting hemizygosity. Similarly, through structural analysis using 3D molecular modeling we have confirmed the potential conformational changes in the protein structure due to mutation c.1207T>A (p.S403T). These findings help us better understand the genetic causes of Intellectual Disabilities (ID) in consanguineous populations, which are crucial for early diagnosis and personalized therapeutic strategies.

PDF

References

1. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, 5th ed. Washington, DC: American Psychiatric Association; 2013.

2. Gécz J, Shoubridge C, Corbett M. The genetic landscape of intellectual disability arising from chromosome X. Trends Genet. 2009;25(7):308–16.

3. Jha A, Rasool IG, Zahoor MY, Iqbal M, Anjum AA, Ashraf F. Whole exome sequencing revealed novel variants in consanguineous Pakistani families with intellectual disability. Genes Genomics. 2021;43(5):503–12.

4. Vissers LELM, Jansen S, de Vries BB. The genetics of intellectual disability. Brain Sci. 2023;13(2):231.

5. Ilyas M, Efthymiou S, Salpietro V, Noureen N, Zafar F, Rauf S. Novel variants underlying autosomal recessive intellectual disability in Pakistani consanguineous families. BMC Med Genet. 2020;21:59.

6. Levy T, Siper PM, Lerman B, Halpern D, Zweifach J, Belani P, et al. DDX3X Syndrome: Summary of Findings and Recommendations for Evaluation and Care. Pediatr Neurol. 2023;138:87–94.

7. Bittles AH, Black ML. Consanguinity, human evolution, and complex diseases. Proc Natl Acad Sci U S A. 2010;107(Suppl 1):1779–86.

8. Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics. 2009;25:1754–1760.

9. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N. The Sequence Alignment/Map format and SAMtools. Bioinformatics. 2009;25:2078–2079.

10. McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 2010;20:1297–1303.

11. Wang K, Li M, Hakonarson H. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 2010;38:e164.

12. Schwarz JM, Cooper DN, Schuelke M, Seelow D. MutationTaster2: mutation prediction for the deep-sequencing age. Nat Methods. 2014;11:361–362.

13. Ng PC, Henikoff S. SIFT: predicting amino acid changes that affect protein function. Nucleic Acids Res. 2003;31:3812–3814.

14. Adzhubei IA, Schmidt S, Peshkin L, Ramensky VE, Gerasimova A, Bork P, et al. A method and server for predicting damaging missense mutations. Nat Methods. 2010;7:248–249. 1000 Genomes Project Consortium, Auton A, Brooks LD, Durbin RM, Garrison EP, Kang HM. A global reference for human genetic variation. Nature. 2015;526:68–74.

15. Sherry ST, Ward MH, Kholodov M, Baker J, Phan L, Smigielski EM. dbSNP: the NCBI database of genetic variation. Nucleic Acids Res. 2001;29:308–311.

16. Karczewski KJ, Francioli LC, Tiao G, Cummings BB, Alföldi J, Wang Q, et al. The mutational constraint spectrum quantified from variation in 141,456 humans. Nature. 2020;581:434–443.

17. Jumper J, Evans R, Pritzel A, Green T, Figurnov M, Ronneberger O, et al. Highly accurate protein structure prediction with AlphaFold. Nature. 2021;596:583–589.

18. Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM, Meng EC, Ferrin TE. UCSF Chimera—a visualization system for exploratory research and analysis. J Comput Chem. 2004;25:1605–1612.

19. Nguyen T, Lee JH, Martinez A, Smith LM, Patel R. Multisystem involvement in X linked intellectual disability syndromes: a clinical cohort analysis. J Med Genet. 2019;56(4):245–53.

20. Jones DM, Ahmed S, Chen Y, Roberts KJ. Phenotypic expansion in neurodevelopmental genetic disorders: implications for diagnosis. Clin Genet. 2021;99(2):123–34.

21. Smith LM, Patel R. Functional relevance of SLC9A7 in neuronal development and synaptic regulation. Neurogenetics. 2020;21(3):189–97.

22. Lee JH, Garcia M, Khan S, O’Connell P, Zhao L. Missense mutations in SLC9A7 associated with intellectual disability and ocular abnormalities: a case series. Hum Mol Genet. 2022;31(10):1745–55.

23. Wang Y, Xiong Q. Integrating clinical and structural data for pathogenic characterization in rare neurodevelopmental disorders. Front Genet. 2018;9:667.

24. Kumar A, Li J, Rossi F, Shen Y. Functional modeling approaches in neurogenetic variant characterization. Mol Neurobiol. 2021;58(9):4445–59.

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright (c) 2026 Pak-Euro Journal of Medical and Life Sciences