Cholesteryl Ester Transfer Protein (CETP) I405V (rs5882) Polymorphism Affects Plasma Lipid Parameters and Lipoprotein Ratio in Hyperlipidemic Ischemic Stroke Patients Article Swipe
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· 2022
· Open Access
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· DOI: https://doi.org/10.9734/ijbcrr/2022/v31i10782
Background: High-density lipoprotein cholesterol (HDL-C) and other lipoproteins are metabolized in part by the cholesteryl ester transport protein (CETP). Cardiovascular risk and the occurrence of ischemic stroke are linked to polymorphism in the CETP gene. Methodology: For the study, 100 ischemic stroke patients and 100 controls with matched sexes and ages ranging from 46 to 87 were chosen. Lipoprotein ratios were computed using Excel software, and lipid parameters were evaluated using Randox diagnostic kits. Polymerase Chain Reaction and Restriction Fragment Length Polymorphism (PCR-RFLP) and 2% gel electrophoresis were used to genotype the CETP gene. The genotyping of the CETP gene were performed by Polymerase Chain Reaction and Restriction Fragment Length Polymorphism (PCR-RFLP) combined with 2% gel electrophoresis. Results: There were significant difference (P<0.0001) in the genotypic and allelic frequencies of CETP SNP between the healthy and patients with ischemic stroke. The frequencies of I/I, I/V and V/V genotypes of the CETP gene were 48%, 37% and 15% for the control and 17%, 33% and 50%, for the stroke subjects, respectively. The frequencies of I and V alleles were 67% and 33% for the control and 37.5% and 62.5% for the stroke subjects, respectively. The V allele carriers of CETP gene had higher plasma TC, TG, VLDL-C, LDL-C, Non-HDL-C, defective HDL-C, HDL2-C and HDL3-C when compared to the I allele carriers for both subjects. The V allele carriers were responsible for the increase in dyslipidemia for both subjects. Conclusion: The results of this study show that mutation of CETP I405V (rs5882) polymorphism causes an increased in plasma TC, TG, VLDL-C, LDL-C, Non-HDL-C, defective HDL-C, HDL2-C and HDL3-C concentration and is associated with an increased risk of ischemic stroke.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.9734/ijbcrr/2022/v31i10782
- https://journalijbcrr.com/index.php/IJBCRR/article/download/782/1565
- OA Status
- diamond
- References
- 31
- Related Works
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- OpenAlex ID
- https://openalex.org/W4308451818
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https://openalex.org/W4308451818Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.9734/ijbcrr/2022/v31i10782Digital Object Identifier
- Title
-
Cholesteryl Ester Transfer Protein (CETP) I405V (rs5882) Polymorphism Affects Plasma Lipid Parameters and Lipoprotein Ratio in Hyperlipidemic Ischemic Stroke PatientsWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2022Year of publication
- Publication date
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2022-11-07Full publication date if available
- Authors
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Johnson Oshiobugie Momoh, Kolawole Gbemavo GodonuList of authors in order
- Landing page
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https://doi.org/10.9734/ijbcrr/2022/v31i10782Publisher landing page
- PDF URL
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https://journalijbcrr.com/index.php/IJBCRR/article/download/782/1565Direct link to full text PDF
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YesWhether a free full text is available
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diamondOpen access status per OpenAlex
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https://journalijbcrr.com/index.php/IJBCRR/article/download/782/1565Direct OA link when available
- Concepts
-
Cholesterylester transfer protein, Genotype, Internal medicine, Allele, Genotyping, Endocrinology, Dyslipidemia, Lipoprotein, Restriction fragment length polymorphism, Polymorphism (computer science), Cholesterol, Medicine, Biology, Genetics, Gene, DiseaseTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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31Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.and | 5, 21, 43, 49, 65, 77, 83, 106, 126, 135, 145, 155, 160, 163, 174, 179, 184, 186, 211, 264, 267 |
| abstract_inverted_index.are | 8, 27 |
| abstract_inverted_index.for | 157, 165, 181, 188, 220, 229, 234 |
| abstract_inverted_index.gel | 85, 115 |
| abstract_inverted_index.had | 200 |
| abstract_inverted_index.the | 13, 22, 32, 37, 91, 97, 124, 133, 149, 158, 166, 182, 189, 216, 230 |
| abstract_inverted_index.17%, | 161 |
| abstract_inverted_index.48%, | 153 |
| abstract_inverted_index.50%, | 164 |
| abstract_inverted_index.CETP | 33, 92, 98, 130, 150, 198, 247 |
| abstract_inverted_index.I/I, | 143 |
| abstract_inverted_index.ages | 50 |
| abstract_inverted_index.both | 221, 235 |
| abstract_inverted_index.from | 52 |
| abstract_inverted_index.gene | 99, 151, 199 |
| abstract_inverted_index.part | 11 |
| abstract_inverted_index.risk | 20, 273 |
| abstract_inverted_index.show | 243 |
| abstract_inverted_index.that | 244 |
| abstract_inverted_index.this | 241 |
| abstract_inverted_index.used | 88 |
| abstract_inverted_index.were | 56, 60, 68, 87, 100, 119, 152, 177, 227 |
| abstract_inverted_index.when | 213 |
| abstract_inverted_index.with | 46, 113, 137, 270 |
| abstract_inverted_index.37.5% | 185 |
| abstract_inverted_index.62.5% | 187 |
| abstract_inverted_index.Chain | 75, 104 |
| abstract_inverted_index.Excel | 63 |
| abstract_inverted_index.I405V | 248 |
| abstract_inverted_index.There | 118 |
| abstract_inverted_index.ester | 15 |
| abstract_inverted_index.gene. | 93 |
| abstract_inverted_index.kits. | 73 |
| abstract_inverted_index.lipid | 66 |
| abstract_inverted_index.other | 6 |
| abstract_inverted_index.sexes | 48 |
| abstract_inverted_index.study | 242 |
| abstract_inverted_index.using | 62, 70 |
| abstract_inverted_index.HDL-C, | 209, 262 |
| abstract_inverted_index.HDL2-C | 210, 263 |
| abstract_inverted_index.HDL3-C | 212, 265 |
| abstract_inverted_index.LDL-C, | 206, 259 |
| abstract_inverted_index.Length | 80, 109 |
| abstract_inverted_index.Randox | 71 |
| abstract_inverted_index.allele | 195, 218, 225 |
| abstract_inverted_index.causes | 251 |
| abstract_inverted_index.higher | 201 |
| abstract_inverted_index.linked | 28 |
| abstract_inverted_index.plasma | 202, 255 |
| abstract_inverted_index.ratios | 59 |
| abstract_inverted_index.stroke | 26, 41, 167, 190 |
| abstract_inverted_index.study, | 38 |
| abstract_inverted_index.(CETP). | 18 |
| abstract_inverted_index.(HDL-C) | 4 |
| abstract_inverted_index.VLDL-C, | 205, 258 |
| abstract_inverted_index.alleles | 176 |
| abstract_inverted_index.allelic | 127 |
| abstract_inverted_index.between | 132 |
| abstract_inverted_index.chosen. | 57 |
| abstract_inverted_index.control | 159, 183 |
| abstract_inverted_index.healthy | 134 |
| abstract_inverted_index.matched | 47 |
| abstract_inverted_index.protein | 17 |
| abstract_inverted_index.ranging | 51 |
| abstract_inverted_index.results | 239 |
| abstract_inverted_index.stroke. | 139, 276 |
| abstract_inverted_index.(rs5882) | 249 |
| abstract_inverted_index.Fragment | 79, 108 |
| abstract_inverted_index.Reaction | 76, 105 |
| abstract_inverted_index.Results: | 117 |
| abstract_inverted_index.carriers | 196, 219, 226 |
| abstract_inverted_index.combined | 112 |
| abstract_inverted_index.compared | 214 |
| abstract_inverted_index.computed | 61 |
| abstract_inverted_index.controls | 45 |
| abstract_inverted_index.genotype | 90 |
| abstract_inverted_index.increase | 231 |
| abstract_inverted_index.ischemic | 25, 40, 138, 275 |
| abstract_inverted_index.mutation | 245 |
| abstract_inverted_index.patients | 42, 136 |
| abstract_inverted_index.defective | 208, 261 |
| abstract_inverted_index.evaluated | 69 |
| abstract_inverted_index.genotypes | 147 |
| abstract_inverted_index.genotypic | 125 |
| abstract_inverted_index.increased | 253, 272 |
| abstract_inverted_index.performed | 101 |
| abstract_inverted_index.software, | 64 |
| abstract_inverted_index.subjects, | 168, 191 |
| abstract_inverted_index.subjects. | 222 |
| abstract_inverted_index.transport | 16 |
| abstract_inverted_index.(PCR-RFLP) | 82, 111 |
| abstract_inverted_index.Non-HDL-C, | 207, 260 |
| abstract_inverted_index.Polymerase | 74, 103 |
| abstract_inverted_index.associated | 269 |
| abstract_inverted_index.diagnostic | 72 |
| abstract_inverted_index.difference | 121 |
| abstract_inverted_index.genotyping | 95 |
| abstract_inverted_index.occurrence | 23 |
| abstract_inverted_index.parameters | 67 |
| abstract_inverted_index.Background: | 0 |
| abstract_inverted_index.Conclusion: | 237 |
| abstract_inverted_index.Lipoprotein | 58 |
| abstract_inverted_index.Restriction | 78, 107 |
| abstract_inverted_index.cholesterol | 3 |
| abstract_inverted_index.cholesteryl | 14 |
| abstract_inverted_index.frequencies | 128, 141, 171 |
| abstract_inverted_index.gene.
 | 34 |
| abstract_inverted_index.lipoprotein | 2 |
| abstract_inverted_index.metabolized | 9 |
| abstract_inverted_index.responsible | 228 |
| abstract_inverted_index.significant | 120 |
| abstract_inverted_index.High-density | 1 |
| abstract_inverted_index.Methodology: | 35 |
| abstract_inverted_index.Polymorphism | 81, 110 |
| abstract_inverted_index.dyslipidemia | 233 |
| abstract_inverted_index.lipoproteins | 7 |
| abstract_inverted_index.polymorphism | 30, 250 |
| abstract_inverted_index.(P<0.0001) | 122 |
| abstract_inverted_index.concentration | 266 |
| abstract_inverted_index.respectively. | 169, 192 |
| abstract_inverted_index.Cardiovascular | 19 |
| abstract_inverted_index.electrophoresis | 86 |
| abstract_inverted_index.subjects.
 | 236 |
| abstract_inverted_index.electrophoresis.
 | 116 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 2 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/3 |
| sustainable_development_goals[0].score | 0.6299999952316284 |
| sustainable_development_goals[0].display_name | Good health and well-being |
| citation_normalized_percentile.value | 0.18486468 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |