Compound Homozygous Rare Mutations in PLCE1 and HPS1 Genes Associated with Autosomal Recessive Retinitis Pigmentosa in Pakistani Families
-
Masroor Ellahi Babar
,
Akhtar Ali
,
Syed Hassan Abbas
,
Mirza Jawad ul Hasnain
,
Nida Babar
,
Hira Babar
,
Tanveer Hussain
,
Asif Nadeem
,
Namra Ayub
,
Sundus Shahid
,
Muhammad Tariq Pervez
Abstract
Background: Retinitis pigmentosa (RP) belongs to pigmentary retinopathies, a generic name for all retinal dystrophies with a major phenotypical and genotypical variation, characterized by progressive reduction of photoreceptor functionality of the rod and cone. Global prevalence of RP is ~ 1/4000 and it can be inherited as autosomal dominant (adRP), autosomal recessive (arRP) or X- linked (xlRP). We designed this study to identify causative mutations in Pakistani families affected with arRP.
Methods: In 2019, we recruited two unrelated Pakistani consanguineous families affected with progressive vision loss and night blindness from Punjab region. Clinical diagnosis confirmed the; bone spicule pigmentation of the retina, and an altered electroretinogram (EGR) response. Proband and healthy individual from each family were subjected for whole-exome sequencing (WES). Various computational tools were used to analyze the Next Generation Sequencing (NGS) data and to predict the pathogenicity of the identified mutations.
Results: WES data analysis highlighted two missense homozygous variants at position c.T1405A (p.S469T) in PLCE1 and c.T11C (p.V4A) in HPS1 genes in proband of both families. Healthy individuals of two families were tested negative for p.S469T and p.V4A mutations. The variant analysis study including molecular dynamic simulations predicted mutations as disease causing.
Conclusion: Compound effect of mutations in rarely linked PLCE1 and HPS1 genes could also cause RP. This study highlights the potential application of WES for a rapid and precise molecular diagnosis for heterogeneous genetic diseases such as RP.
1. Dias MF, Joo K, Kemp JA, Fialho SL, da Silva Cunha A, Woo SJ, et al. Molecular genetics and emerging therapies for retinitis pigmentosa: Basic research and clinical perspectives. Prog Retin Eye Res [Internet]. 2018;63(October 2017):107–31. Available from: https://doi.org/10.1016/j.preteyeres.2017.10.004
2. Estrada-Cuzcano A, Neveling K, Kohl S, Banin E, Rotenstreich Y, Sharon D, et al. Mutations in C8orf37, encoding a ciliary protein, are associated with autosomal-recessive retinal dystrophies with early macular involvement. Am J Hum Genet. 2012;90(1):102–9.
3. Bovolenta P, Cisneros E. Retinitis pigmentosa: Cone photoreceptors starving to death. Nat Neurosci. 2009;12(1):5–6.
4. Davis BM, Crawley L, Pahlitzsch M, Javaid F, Cordeiro MF. Glaucoma: the retina and beyond. Acta Neuropathol. 2016;132(6):807–26.
5. Altintas N, Sarica Yilmaz Ö, Soylu A, Biçer I. Analysis of mutations of Retinitis pigmentosa by sequencing. J Appl Biol Sci. 2017;11(1):11–4.
6. Takahashi VKL, Takiuti JT, Carvalho-Jr JRL, Xu CL, Duong JK, Mahajan VB, et al. Fundus autofluorescence and ellipsoid zone (EZ) line width can be an outcome measurement in RHO-associated autosomal dominant retinitis pigmentosa. Graefe’s Arch Clin Exp Ophthalmol. 2019;257(4):725–31.
7. Daiger SP, Bowne SJ, Sullivan LS. Genes and mutations causing autosomal dominant retinitis pigmentosa. Cold Spring Harb Perspect Med. 2015;5(10):1–13.
8. Gorbatyuk MS, Starr CR, Gorbatyuk OS. Endoplasmic reticulum stress: New insights into the pathogenesis and treatment of retinal degenerative diseases. Prog Retin Eye Res [Internet]. 2020;(March):100860. Available from: https://doi.org/10.1016/j.preteyeres.2020.100860
9. Pichi F, Abboud EB, Ghazi NG, Khan AO. Fundus autofluorescence imaging in hereditary retinal diseases. Acta Ophthalmol. 2018;96(5):e549–61.
10. Wang M, Wang N, Li X, Wang G. A distinct form of retinitis pigmentosa with retinal vascular occlusion. Int J Clin Exp Med. 2018;11(6):5802–10.
11. Picaud S, Dalkara D, Marazova K, Goureau O, Roska B, Sahel JA. The primate model for understanding and restoring vision. Proc Natl Acad Sci U S A. 2019;116(52):26280–7.
12. El Shamieh S, Neuillé M, Terray A, Orhan E, Condroyer C, Démontant V, et al. Whole-exome sequencing identifies kiz as a ciliary gene associated with autosomal-recessive rod-cone dystrophy. Am J Hum Genet. 2014;94(4):625–33.
13. Hashmi MA. Frequency of consanguinity and its effect on congenital malformation--a hospital based study. J Pak Med Assoc. 1997;47(3):75–8.
14. Angural A, Spolia A, Mahajan A, Verma V, Sharma A, Kumar P, et al. Review: Understanding Rare Genetic Diseases in Low Resource Regions Like Jammu and Kashmir – India. Front Genet. 2020;11(April):1–18.
15. Li H, Durbin R. Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics. 2010;26(5):589–95.
16. Koboldt DC, Chen K, Wylie T, Larson DE, McLellan MD, Mardis ER, et al. VarScan: Variant detection in massively parallel sequencing of individual and pooled samples. Bioinformatics. 2009;25(17):2283–5.
17. 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. Genome Res. 2010;20(9):1297–303.
18. Van der Auwera GA, Carneiro MO, Hartl C, Poplin R, del Angel G, Levy-Moonshine A, et al. From fastQ data to high-confidence variant calls: The genome analysis toolkit best practices pipeline. Current Protocols in Bioinformatics. 2013. 1–33 p.
19. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics. 2009;25(16):2078–9.
20. Wang K, Li M, Hakonarson H. ANNOVAR: Functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 2010;38(16):1–7.
21. Chang X, Wang K. Wannovar: Annotating genetic variants for personal genomes via the web. J Med Genet. 2012;49(7):433–6.
22. Clarke L, Zheng-Bradley X, Smith R, Kulesha E, Xiao C, Toneva I, et al. The 1000 Genomes Pproject: Data management and community access. Nat Methods. 2012;9(5):1–4.
23. Ng PC, Henikoff S. SIFT: Predicting amino acid changes that affect protein function. Nucleic Acids Res. 2003;31(13):3812–4.
24. Clemens DJ, Lentino AR, Kapplinger JD, Ye D, Zhou W, Tester DJ, et al. Using the genome aggregation database, computational pathogenicity prediction tools, and patch clamp heterologous expression studies to demote previously published long QT syndrome type 1 mutations from pathogenic to benign. Hear Rhythm [Internet]. 2018;15(4):555–61. Available from: https://doi.org/10.1016/j.hrthm.2017.11.032
25. Choi Y, Sims GE, Murphy S, Miller JR, Chan AP. Predicting the Functional Effect of Amino Acid Substitutions and Indels. PLoS One. 2012;7(10).
26. Adzhubei I, Jordan DM, Sunyaev SR. Predicting functional effect of human missense mutations using PolyPhen-2. Current Protocols in Human Genetics. 2013. 1–41 p.
27. Auer PL, Johnsen JM, Johnson AD, Logsdon BA, Lange LA, Nalls MA, et al. Imputation of exome sequence variants into population-based samples and blood-cell-trait-associated loci in african americans: NHLBI GO exome sequencing project. Am J Hum Genet [Internet]. 2012;91(5):794–808. Available from: http://dx.doi.org/10.1016/j.ajhg.2012.08.031
28. Chun S, Fay JC. Identification of deleterious mutations within three human genomes. Genome Res. 2009;19(9):1553–61.
29. Panadés-de Oliveira L, Montoya J, Emperador S, Ruiz-Pesini E, Jericó I, Arenas J, et al. A novel mutation in the mitochondrial MT-ND5 gene in a family with MELAS. The relevance of genetic analysis on targeted tissues. Mitochondrion [Internet]. 2020;50:14–8. Available from: https://doi.org/10.1016/j.mito.2019.10.001
30. Palumbo D, Affinito O, Monticelli A, Cocozza S. DNA Methylation variability among individuals is related to CpGs cluster density and evolutionary signatures. BMC Genomics. 2018;19(1):1–9.
31. Ávila-Fernández A, Cantalapiedra D, Aller E, Vallespín E, Aguirre-Lambán J, Blanco-Kelly F, et al. Mutation analysis of 272 Spanish families affected by autosomal recessive retinitis pigmentosa using a genotyping microarray. Mol Vis. 2010;16(December):2550–8.
32. Schmidt M, Evellin S, Weernink PAO, vom Dorp F, Rehmann H, Lomasney JW, et al. A new phospholipase-C-calcium signalling pathway mediated by cyclic AMP and a Rap GTPase. Nat Cell Biol. 2001;3(11):1020–4.
33. Hartong DT, Berson EL, Dryja TP. Retinitis pigmentosa. 2006;1795–809.
34. Zhang CL, Zou Y, Yu RT, Gage FH, Evans RM. Nuclear receptor TLX prevents retinal dystrophy and recruits the corepressor atrophin1. Genes Dev. 2006;20(10):1308–20.
35. Mitchell DC, Bryan BA, Liu JP, Liu W Bin, Zhang L, Qu J, et al. Developmental expression of three small GTPases in the mouse eye. Mol Vis. 2007;13(June):1144–53.
36. Sadowski CE, Lovric S, Ashraf S, Pabst WL, Gee HY, Kohl S, et al. A single-gene cause in 29.5% of cases of steroid-resistant nephrotic syndrome. J Am Soc Nephrol. 2015;26(6):1279–89.
37. Gbadegesin R, Hinkes BG, Hoskins BE, Vlangos CN, Heeringa SF, Liu J, et al. Mutations in PLCE1 are a major cause of isolated diffuse mesangial sclerosis (IDMS). Nephrol Dial Transplant. 2008;23(4):1291–7.
38. Shimizu M, Irabu H, Kaneda H, Ohta K, Nozu K. Familial focal segmental glomerulosclerosis with PLCE1 mutation in siblings. Pediatr Int. 2019;61(7):726–7.
39. Nazarian R, Falcón-Pérez JM, Dell’Angelica EC. Biogenesis of lysosome-related organelles complex 3 (BLOC-3): A complex containing the Hermansky-Pudlak syndrome (HPS) proteins HPS1 and HPS4. Proc Natl Acad Sci U S A. 2003;100(15):8770–5.
40. Marks MS, Seabra MC. The melanosome: Membrane dynamics in black and white. Nat Rev Mol Cell Biol. 2001;2(10):738–48.
41. Horikawa T, Araki K, Fukai K, Ueda M, Ueda T, Ito S, et al. Heterozygous HPS1 mutations in a case of Hermansky-Pudlak syndrome with giant melanosomes. Br J Dermatol. 2000;143(3):635–40.
42. Ul Hasnain MJ, Shoaib M, Qadri S, Afzal B, Anwar T, Abbas SH, et al. Computational analysis of functional single nucleotide polymorphisms associated with SLC26A4 gene. PLoS One. 2020;15(1):225368.
43. Xiao X, Mai G, Li S, Guo X, Zhang Q. Identification of CYP4V2 mutation in 21 families and overview of mutation spectrum in Bietti crystalline corneoretinal dystrophy. Biochem Biophys Res Commun. 2011;409(2):181–6.
2. Estrada-Cuzcano A, Neveling K, Kohl S, Banin E, Rotenstreich Y, Sharon D, et al. Mutations in C8orf37, encoding a ciliary protein, are associated with autosomal-recessive retinal dystrophies with early macular involvement. Am J Hum Genet. 2012;90(1):102–9.
3. Bovolenta P, Cisneros E. Retinitis pigmentosa: Cone photoreceptors starving to death. Nat Neurosci. 2009;12(1):5–6.
4. Davis BM, Crawley L, Pahlitzsch M, Javaid F, Cordeiro MF. Glaucoma: the retina and beyond. Acta Neuropathol. 2016;132(6):807–26.
5. Altintas N, Sarica Yilmaz Ö, Soylu A, Biçer I. Analysis of mutations of Retinitis pigmentosa by sequencing. J Appl Biol Sci. 2017;11(1):11–4.
6. Takahashi VKL, Takiuti JT, Carvalho-Jr JRL, Xu CL, Duong JK, Mahajan VB, et al. Fundus autofluorescence and ellipsoid zone (EZ) line width can be an outcome measurement in RHO-associated autosomal dominant retinitis pigmentosa. Graefe’s Arch Clin Exp Ophthalmol. 2019;257(4):725–31.
7. Daiger SP, Bowne SJ, Sullivan LS. Genes and mutations causing autosomal dominant retinitis pigmentosa. Cold Spring Harb Perspect Med. 2015;5(10):1–13.
8. Gorbatyuk MS, Starr CR, Gorbatyuk OS. Endoplasmic reticulum stress: New insights into the pathogenesis and treatment of retinal degenerative diseases. Prog Retin Eye Res [Internet]. 2020;(March):100860. Available from: https://doi.org/10.1016/j.preteyeres.2020.100860
9. Pichi F, Abboud EB, Ghazi NG, Khan AO. Fundus autofluorescence imaging in hereditary retinal diseases. Acta Ophthalmol. 2018;96(5):e549–61.
10. Wang M, Wang N, Li X, Wang G. A distinct form of retinitis pigmentosa with retinal vascular occlusion. Int J Clin Exp Med. 2018;11(6):5802–10.
11. Picaud S, Dalkara D, Marazova K, Goureau O, Roska B, Sahel JA. The primate model for understanding and restoring vision. Proc Natl Acad Sci U S A. 2019;116(52):26280–7.
12. El Shamieh S, Neuillé M, Terray A, Orhan E, Condroyer C, Démontant V, et al. Whole-exome sequencing identifies kiz as a ciliary gene associated with autosomal-recessive rod-cone dystrophy. Am J Hum Genet. 2014;94(4):625–33.
13. Hashmi MA. Frequency of consanguinity and its effect on congenital malformation--a hospital based study. J Pak Med Assoc. 1997;47(3):75–8.
14. Angural A, Spolia A, Mahajan A, Verma V, Sharma A, Kumar P, et al. Review: Understanding Rare Genetic Diseases in Low Resource Regions Like Jammu and Kashmir – India. Front Genet. 2020;11(April):1–18.
15. Li H, Durbin R. Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics. 2010;26(5):589–95.
16. Koboldt DC, Chen K, Wylie T, Larson DE, McLellan MD, Mardis ER, et al. VarScan: Variant detection in massively parallel sequencing of individual and pooled samples. Bioinformatics. 2009;25(17):2283–5.
17. 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. Genome Res. 2010;20(9):1297–303.
18. Van der Auwera GA, Carneiro MO, Hartl C, Poplin R, del Angel G, Levy-Moonshine A, et al. From fastQ data to high-confidence variant calls: The genome analysis toolkit best practices pipeline. Current Protocols in Bioinformatics. 2013. 1–33 p.
19. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics. 2009;25(16):2078–9.
20. Wang K, Li M, Hakonarson H. ANNOVAR: Functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 2010;38(16):1–7.
21. Chang X, Wang K. Wannovar: Annotating genetic variants for personal genomes via the web. J Med Genet. 2012;49(7):433–6.
22. Clarke L, Zheng-Bradley X, Smith R, Kulesha E, Xiao C, Toneva I, et al. The 1000 Genomes Pproject: Data management and community access. Nat Methods. 2012;9(5):1–4.
23. Ng PC, Henikoff S. SIFT: Predicting amino acid changes that affect protein function. Nucleic Acids Res. 2003;31(13):3812–4.
24. Clemens DJ, Lentino AR, Kapplinger JD, Ye D, Zhou W, Tester DJ, et al. Using the genome aggregation database, computational pathogenicity prediction tools, and patch clamp heterologous expression studies to demote previously published long QT syndrome type 1 mutations from pathogenic to benign. Hear Rhythm [Internet]. 2018;15(4):555–61. Available from: https://doi.org/10.1016/j.hrthm.2017.11.032
25. Choi Y, Sims GE, Murphy S, Miller JR, Chan AP. Predicting the Functional Effect of Amino Acid Substitutions and Indels. PLoS One. 2012;7(10).
26. Adzhubei I, Jordan DM, Sunyaev SR. Predicting functional effect of human missense mutations using PolyPhen-2. Current Protocols in Human Genetics. 2013. 1–41 p.
27. Auer PL, Johnsen JM, Johnson AD, Logsdon BA, Lange LA, Nalls MA, et al. Imputation of exome sequence variants into population-based samples and blood-cell-trait-associated loci in african americans: NHLBI GO exome sequencing project. Am J Hum Genet [Internet]. 2012;91(5):794–808. Available from: http://dx.doi.org/10.1016/j.ajhg.2012.08.031
28. Chun S, Fay JC. Identification of deleterious mutations within three human genomes. Genome Res. 2009;19(9):1553–61.
29. Panadés-de Oliveira L, Montoya J, Emperador S, Ruiz-Pesini E, Jericó I, Arenas J, et al. A novel mutation in the mitochondrial MT-ND5 gene in a family with MELAS. The relevance of genetic analysis on targeted tissues. Mitochondrion [Internet]. 2020;50:14–8. Available from: https://doi.org/10.1016/j.mito.2019.10.001
30. Palumbo D, Affinito O, Monticelli A, Cocozza S. DNA Methylation variability among individuals is related to CpGs cluster density and evolutionary signatures. BMC Genomics. 2018;19(1):1–9.
31. Ávila-Fernández A, Cantalapiedra D, Aller E, Vallespín E, Aguirre-Lambán J, Blanco-Kelly F, et al. Mutation analysis of 272 Spanish families affected by autosomal recessive retinitis pigmentosa using a genotyping microarray. Mol Vis. 2010;16(December):2550–8.
32. Schmidt M, Evellin S, Weernink PAO, vom Dorp F, Rehmann H, Lomasney JW, et al. A new phospholipase-C-calcium signalling pathway mediated by cyclic AMP and a Rap GTPase. Nat Cell Biol. 2001;3(11):1020–4.
33. Hartong DT, Berson EL, Dryja TP. Retinitis pigmentosa. 2006;1795–809.
34. Zhang CL, Zou Y, Yu RT, Gage FH, Evans RM. Nuclear receptor TLX prevents retinal dystrophy and recruits the corepressor atrophin1. Genes Dev. 2006;20(10):1308–20.
35. Mitchell DC, Bryan BA, Liu JP, Liu W Bin, Zhang L, Qu J, et al. Developmental expression of three small GTPases in the mouse eye. Mol Vis. 2007;13(June):1144–53.
36. Sadowski CE, Lovric S, Ashraf S, Pabst WL, Gee HY, Kohl S, et al. A single-gene cause in 29.5% of cases of steroid-resistant nephrotic syndrome. J Am Soc Nephrol. 2015;26(6):1279–89.
37. Gbadegesin R, Hinkes BG, Hoskins BE, Vlangos CN, Heeringa SF, Liu J, et al. Mutations in PLCE1 are a major cause of isolated diffuse mesangial sclerosis (IDMS). Nephrol Dial Transplant. 2008;23(4):1291–7.
38. Shimizu M, Irabu H, Kaneda H, Ohta K, Nozu K. Familial focal segmental glomerulosclerosis with PLCE1 mutation in siblings. Pediatr Int. 2019;61(7):726–7.
39. Nazarian R, Falcón-Pérez JM, Dell’Angelica EC. Biogenesis of lysosome-related organelles complex 3 (BLOC-3): A complex containing the Hermansky-Pudlak syndrome (HPS) proteins HPS1 and HPS4. Proc Natl Acad Sci U S A. 2003;100(15):8770–5.
40. Marks MS, Seabra MC. The melanosome: Membrane dynamics in black and white. Nat Rev Mol Cell Biol. 2001;2(10):738–48.
41. Horikawa T, Araki K, Fukai K, Ueda M, Ueda T, Ito S, et al. Heterozygous HPS1 mutations in a case of Hermansky-Pudlak syndrome with giant melanosomes. Br J Dermatol. 2000;143(3):635–40.
42. Ul Hasnain MJ, Shoaib M, Qadri S, Afzal B, Anwar T, Abbas SH, et al. Computational analysis of functional single nucleotide polymorphisms associated with SLC26A4 gene. PLoS One. 2020;15(1):225368.
43. Xiao X, Mai G, Li S, Guo X, Zhang Q. Identification of CYP4V2 mutation in 21 families and overview of mutation spectrum in Bietti crystalline corneoretinal dystrophy. Biochem Biophys Res Commun. 2011;409(2):181–6.
| Files | ||
| Issue | Vol 51 No 9 (2022) | |
| Section | Original Article(s) | |
| DOI | https://doi.org/10.18502/ijph.v51i9.10560 | |
| Keywords | ||
| Retinitis pigmentosa Whole-exome sequencing Pakistan | ||
| Rights and permissions | |
|
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
How to Cite
1.
Babar M, Ali A, Abbas S, Hasnain M, Babar N, Babar H, Hussain T, Nadeem A, Ayub N, Shahid S, Pervez M. Compound Homozygous Rare Mutations in PLCE1 and HPS1 Genes Associated with Autosomal Recessive Retinitis Pigmentosa in Pakistani Families. Iran J Public Health. 2022;51(9):2048-2059.
