Identification of PCSK9 Gene Mutation in Bangladeshi Population for Prognosis of Cardiovascular Disease
DOI:
https://doi.org/10.14738/aivp.113.14918Keywords:
CVD, Dyslipidemia, Lipid profiling, PCSK9 gene, MutationsAbstract
Cardiovascular Diseases (CVDs) is one of the most common causes of mortality and morbidity in world as well as in Bangladesh. Dyslipidemia or abnormal lipid level leads to atherosclerosis which is one of the major risk factors for developing CVD. The ultimate consequences of CVD include myocardial infarction, heart failure and stroke. Low-density lipoprotein cholesterol levels in the blood are significantly correlated with atherosclerosis progression or continuously building up plaques in inner wall of cardiac artery. The abnormality of HDL and LDL level is greatly influenced by genetic factors. PCSK9 is an endogenous inhibitor of the low-density lipoprotein receptor and plays a significant role in the metabolism of cholesterol. The current study aims to identify the PCSK9 gene mutations as well as to carry out a gross assessment of secondary causes to reveal the actual magnitude of risk for future generation of Bangladeshi population. Blood samples were collected from 100 subjects for lipid profiling and DNA was extracted from the blood of the patients with abnormal lipid profile. Socio-demographic analyses were carried out to assess the magnitude of the risk factors associated with CVD. For mutation analysis of the PCSK9 gene, genomic DNA was extracted from the blood. Exon 1 and 2 were selected for segmental amplification and subsequent genetic analysis. Mutations in the amplified sequences were identified by multiple sequence alignment. Bioinformatics analysis revealed seven point mutations in exon-1 and three point mutations in exon-2 of PCSK9 gene of some of the CVD patients. This study will be helpful to evaluate the possibility of using PCSK9 as genetic markers for prognosis of dyslipidemia and CVD.
References
R. R. Huxley et al., “Age-and sex-specific burden of cardiovascular disease attributable to 5 major and modifiable risk factors in 10 asian countries of the western pacific region,” Circ. J., vol. 79, no. 8, pp. 1662–1674, 2015, doi: 10.1253/circj.CJ-15-0661.
K. Fatema, N. A. Zwar, A. H. Milton, L. Ali, and B. Rahman, “Prevalence of risk factors for cardiovascular diseases in Bangladesh: A systematic review and meta-analysis,” PLoS One, vol. 11, no. 8, pp. 1–14, 2016, doi: 10.1371/journal.pone.0160180.
M. Rafieian-Kopaei, M. Setorki, M. Doudi, A. Baradaran, and H. Nasri, “Atherosclerosis: Process, indicators, risk factors and new hopes,” Int. J. Prev. Med., vol. 5, no. 8, pp. 927–946, 2014.
D. Pahlajani, “Effect of sitagliptin on cardiovascular outcomes in type 2 diabetes,” Yearb. Cardiol. 2016,
R. Garg, “Association of atherosclerosis with dyslipidemia and co-morbid conditions : A descriptive study,” vol. 6, no. 1, 2015, doi: 10.4103/0976-9668.149117.
A. Qasim and D. Rader, “Human genetics of variation in high-density lipoprotein cholesterol,” Curr. Atheroscler. Rep., vol. 8, no. 3, pp. 198–205, 2006, doi: 10.1007/s11883-006-0074-0.
H. Cohen and R. Shamir, “Lipid disorders in children and adolescents,” in Pediatric endocrinology, CRC Press, 2006, pp. 305–316.
S. R. Daniels and S. C. Couch, “Lipid Disorders in Children and Adolescents,” in Sperling Pediatric Endocrinology: Expert Consult - Online and Print, CRC Press, 2020, pp. 1004–1021.
J. D. Horton, J. C. Cohen, and H. H. Hobbs, “PCSK9: A convertase that coordinates LDL catabolism,” J. Lipid Res., vol. 50, no. SUPPL., pp. S172–S177, 2009, doi: 10.1194/jlr.R800091-JLR200.
D. Allard et al., “Novel mutations of the PCSK9 gene cause variable phenotype of autosomal dominant hypercholesterolemia.,” Hum. Mutat., vol. 26, no. 5, p. 497, 2005, doi: 10.1002/humu.9383.
Y. Cho, S. Y. Shin, S. Won, C. L. Relton, G. D. Smith, and M. J. Shin, “Alcohol intake and cardiovascular risk factors: A Mendelian randomisation study,” Sci. Rep., vol. 5, no. 1, p. 18422, 2015, doi: 10.1038/srep18422.
J. Miao et al., “Role of insulin in the regulation of proprotein convertase subtilisin/kexin type 9,” Arterioscler. Thromb. Vasc. Biol., vol. 35, no. 7, pp. 1589–1596, 2015, doi: 10.1161/ATVBAHA.115.305688.
I. Adzhubei, D. M. Jordan, and S. R. Sunyaev, “Predicting functional effect of human missense mutations using PolyPhen-2,” Curr. Protoc. Hum. Genet., vol. 76, no. SUPPL.76, pp. 7–20, 2013, doi: 10.1002/0471142905.hg0720s76.
P. D. Thomas et al., “PANTHER: A library of protein families and subfamilies indexed by function,” Genome Res., vol. 13, no. 9, pp. 2129–2141, 2003, doi: 10.1101/gr.772403.
E. Capriotti, R. Calabrese, and R. Casadio, “Predicting the insurgence of human genetic diseases associated to single point protein mutations with support vector machines and evolutionary information,” Bioinformatics, vol. 22, no. 22, pp. 2729–2734, 2006, doi: 10.1093/bioinformatics/btl423.
R. Calabrese, E. Capriotti, P. Fariselli, P. L. Martelli, and R. Casadio, “Functional annotations improve the predictive score of human disease-related mutations in proteins,” Hum. Mutat., vol. 30, no. 8, pp. 1237–1244, 2009, doi: 10.1002/humu.21047.
J. Cheng, A. Randall, and P. Baldi, “Prediction of protein stability changes for single-site mutations using support vector machines,” Proteins Struct. Funct. Genet., vol. 62, no. 4, pp. 1125–1132, 2006, doi: 10.1002/prot.20810.
D. E. Kim, D. Chivian, and D. Baker, “Protein structure prediction and analysis using the Robetta server,” Nucleic Acids Res., vol. 32, no. WEB SERVER ISS., pp. W526–W531, 2004, doi: 10.1093/nar/gkh468.
C. Colovos and T. O. Yeates, “ERRAT: an empirical atom-based method for validating protein structures,” Protein Sci., vol. 2, no. 9, pp. 1511–1519, 1993.
R. A. Laskowski, M. W. MacArthur, D. S. Moss, and J. M. Thornton, “PROCHECK: a program to check the stereochemical quality of protein structures,” J. Appl. Crystallogr., vol. 26, no. 2, pp. 283–291, 1993, doi: 10.1107/s0021889892009944.
E. F. Pettersen et al., “UCSF ChimeraX: Structure visualization for researchers, educators, and developers,” Protein Sci., vol. 30, no. 1, pp. 70–82, 2021, doi: 10.1002/pro.3943.
E. A. Enas, V. Mohan, M. Deepa, S. Farooq, S. Pazhoor, and H. Chennikkara, “The metabolic syndrome and dyslipidemia among Asian Indians: a population with high rates of diabetes and premature coronary artery disease.,” J. Cardiometab. Syndr., vol. 2, no. 4, pp. 267–275, 2007, doi: 10.1111/j.1559-4564.2007.07392.x.
K. Ball, “The Basis for Action,” pp. 822–826, 1974.
W. Lieb and R. S. Vasan, “Scientific Contributions of Population-Based Studies to Cardiovascular Epidemiology in the GWAS Era,” Front. Cardiovasc. Med., vol. 5, no. June, pp. 1–6, 2018, doi: 10.3389/fcvm.2018.00057.
S. K. Das et al., “Serum Lipid Profile Among Urban and Rural Bangladeshi Population Obesity & Weight Loss Therapy,” vol. 2, no. 8, pp. 8–11, 2012, doi: 10.4172/2165-7904.1000148.
M. Kaplan and M. Aviram, “Oxidized Low Density Lipoprotein : Atherogenic and Proinflammatory Characteristics during Macrophage Foam Cell Formation . An Inhibitory Role for Nutritional Antioxidants and Serum Paraoxonase,” vol. 37, no. 8, pp. 777–787, 1999.
M. Wasay, I. A. Khatri, and S. Kaul, “Stroke in South Asian countries,” Nat. Publ. Gr., vol. 10, no. 3, pp. 135–143, 2014, doi: 10.1038/nrneurol.2014.13.
T. J. Chahil and H. N. Ginsberg, “Diabetic Dyslipidemia,” Endocrinol. Metab. Clin. North Am., vol. 35, no. 3, pp. 491–510, 2006, doi: 10.1016/j.ecl.2006.06.002.
R. Ross and J. Glomset, “Response to Injury and Atherogenesis,” pp. 675–684, 1976.
A. Ashraf et al., “Health and Demographic Surveillance Systems in Asia,” no. May, 2009, doi: 10.3402/gha.v2i0.1997.
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Copyright (c) 2023 Md. Mahbubur Rahman, Md. Tanjil Islam Shovon, Md. Mahmudul Hasan Maruf, Ratna Khatun, Md. Jahangir Alam, Md. Ragib Shariar, Md. Zahidus Sayeed, Zennat Ferdousi, Kazi Md. Faisal Hoque, Khandaker Md. Khalid-Bin-Ferdaus, Md. Abu Reza
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