Cholesteryl Ester Transfer Protein Gene Polymorphism (I405V) and Risk of Ischemic Stroke

Buraczynska, Kinga; Rejdak, Konrad; Buraczyńska, Monika

doi:10.1016/j.jstrokecerebrovasdis.2018.06.020

Cited by 3 publications

(2 citation statements)

References 30 publications

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“…26 out of the 31 loci were potentially novel for the studied phenotypes (Table S14). Female-only meta-analysis for stroke identified the previously reported locus CETP 21 that did not reach the genome-wide significance threshold in the sex-combined meta-analysis. The top hit is an intronic variant rs7499892 with stronger association in females than in males (in females: effect size [SE] = 0.078 [0.014], p = 1.08 3 10 À8 ; in males: effect size [SE] = 0.007 [0.012], p = 0.56).…”

Section: Sex-stratified Meta-analysesmentioning

confidence: 86%

Global Biobank Meta-analysis Initiative: Powering genetic discovery across human disease

Zhou

Kanai²,

Wu³

et al. 2022

Cell Genomics

151

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Section: Sex-stratified Meta-analysesmentioning

confidence: 86%

Global Biobank Meta-analysis Initiative: Powering genetic discovery across human disease

Zhou

Kanai²,

Wu³

et al. 2022

Cell Genomics

151

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“…26 out of the 31 loci are potentially novel for the studied phenotypes (Supplementary Table 13). The female-only meta-analysis for stroke identified the previously reported locus CETP (Buraczynska et al, 2018) that did not reach the genome-wide significance threshold in the sex-combined meta-analysis. The top hit is an intronic rs7499892 variant with stronger association in females than males (in females: effect size (se) = 0.078 (0.014), p-value =1.08x10 -8 , in males effect size (se) = 0.007(0.012), p-value = 0.56) .Previous studies have shown that the transgenic expression of CETP increases plasma triglyceride levels in females and males through distinct mechanisms (Palmisano et al, 2016(Palmisano et al, , 2021.…”

Section: Sex-stratified Meta-analysesmentioning

confidence: 95%

Global Biobank Meta-analysis Initiative: powering genetic discovery across human diseases

Zhou¹,

Kanai²,

Wu³

et al. 2021

Preprint

114

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SummaryBiobanks are being established across the world to understand the genetic, environmental, and epidemiological basis of human diseases with the goal of better prevention and treatments. Genome-wide association studies (GWAS) have been very successful at mapping genomic loci for a wide range of human diseases and traits, but in general, lack appropriate representation of diverse ancestries - with most biobanks and preceding GWAS studies composed of individuals of European ancestries. Here, we introduce the Global Biobank Meta-analysis Initiative (GBMI) -- a collaborative network of 19 biobanks from 4 continents representing more than 2.1 million consented individuals with genetic data linked to electronic health records. GBMI meta-analyzes summary statistics from GWAS generated using harmonized genotypes and phenotypes from member biobanks. GBMI brings together results from GWAS analysis across 6 main ancestry groups: approximately 33,000 of African ancestry either from Africa or from admixed-ancestry diaspora (AFR), 18,000 admixed American (AMR), 31,000 Central and South Asian (CSA), 341,000 East Asian (EAS), 1.4 million European (EUR), and 1,600 Middle Eastern (MID) individuals. In this flagship project, we generated GWASs from across 14 exemplar diseases and endpoints, including both common and less prevalent diseases that were previously understudied. Using the genetic association results, we validate that GWASs conducted in biobanks worldwide can be successfully integrated despite heterogeneity in case definitions, recruitment strategies, and baseline characteristics between biobanks. We demonstrate the value of this collaborative effort to improve GWAS power for diseases, increase representation, benefit understudied diseases, and improve risk prediction while also enabling the nomination of disease genes and drug candidates by incorporating gene and protein expression data and providing insight into the underlying biology of the studied traits.

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Cholesteryl Ester Transfer Protein (CETP) Variations in Relation to Lipid Profiles and Cardiovascular Diseases: An Update

Dabravolski,

Orekhov,

Melnichenko

et al. 2024

CPD

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Lipid metabolism plays an essential role in the pathogenesis of cardiovascular and metabolic diseases. Cholesteryl ester transfer protein (CETP) is a crucial glycoprotein involved in lipid metabolism by transferring cholesteryl esters (CE) and triglycerides (TG) between plasma lipoproteins. CETP activity results in reduced HDL-C and increased VLDL- and LDL-C concentrations, thus increasing the risk of cardiovascular and metabolic diseases. In this review, we discuss the structure of CETP and its mechanism of action. Furthermore, we focus on recent experiments on animal CETP-expressing models, deciphering the regulation and functions of CETP in various genetic backgrounds and interaction with different external factors. Finally, we discuss recent publications revealing the association of CETP single nucleotide polymorphisms (SNPs) with the risk of cardiovascular and metabolic diseases, lifestyle factors, diet and therapeutic interventions. While CETP SNPs can be used as effective diagnostic markers, diet, lifestyle, gender and ethnic specificity should also be considered for effective treatment.

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Cholesteryl Ester Transfer Protein Gene Polymorphism (I405V) and Risk of Ischemic Stroke

Cited by 3 publications

References 30 publications

Global Biobank Meta-analysis Initiative: Powering genetic discovery across human disease

Global Biobank Meta-analysis Initiative: Powering genetic discovery across human disease

Global Biobank Meta-analysis Initiative: powering genetic discovery across human diseases

Cholesteryl Ester Transfer Protein (CETP) Variations in Relation to Lipid Profiles and Cardiovascular Diseases: An Update

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