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