Re-sequencing of the APOAI promoter region and the genetic association of the -75G &gt; A polymorphism with increased cholesterol and low density lipoprotein levels among a sample of the Kuwaiti population

Al-Bustan, Suzanne A.; Al-Serri, Ahmad; Annice, Babitha G.; Alnaqeeb, Majed A.; Ebrahim, Ghada A

doi:10.1186/1471-2350-14-90

Cited by 16 publications

(18 citation statements)

References 51 publications

(82 reference statements)

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“…Among these results, two regions (in ENSG00000255599 and ENSG00000260254) on chromosome 11 located on 11q23.2 adjacently replicate the findings in that Canadian study, which reports the suggestive genome-wide regions related to LDL-C level. More recently, the variants in APOA1/APOC3/APOA4/APOA5 gene cluster located near these regions have been found associated with LDL-C level [Al-Bustan et al, 2013;Pollin et al, 2008]. Furthermore, the finding of two gene regions on chromosome 19 (in ENSG00000104866 and ENSG00000213889) located from 45.6 to 46.0 Mb also supports the region identified in the Canadian study.…”

Section: Ldl-c Studysupporting

confidence: 69%

Bayesian Latent Variable Collapsing Model for Detecting Rare Variant Interaction Effect in Twin Study

Sillanpää

Ripatti

et al. 2014

Genetic Epidemiology

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By analyzing more next-generation sequencing data, researchers have affirmed that rare genetic variants are widespread among populations and likely play an important role in complex phenotypes. Recently, a handful of statistical models have been developed to analyze rare variant (RV) association in different study designs. However, due to the scarce occurrence of minor alleles in data, appropriate statistical methods for detecting RV interaction effects are still difficult to develop. We propose a hierarchical Bayesian latent variable collapsing method (BLVCM), which circumvents the obstacles by parameterizing the signals of RVs with latent variables in a Bayesian framework and is parameterized for twin data. The BLVCM can tackle nonassociated variants, allow both protective and deleterious effects, capture SNP-SNP synergistic effect, provide estimates for the gene level and individual SNP contributions, and can be applied to both independent and various twin designs. We assessed the statistical properties of the BLVCM using simulated data, and found that it achieved better performance in terms of power for interaction effect detection compared to the Granvil and the SKAT. As proof of practical application, the BLVCM was then applied to a twin study analysis of more than 20,000 gene regions to identify significant RVs associated with low-density lipoprotein cholesterol level. The results show that some of the findings are consistent with previous studies, and we identified some novel gene regions with significant SNP-SNP synergistic effects.

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Section: Ldl-c Studysupporting

confidence: 69%

Bayesian Latent Variable Collapsing Model for Detecting Rare Variant Interaction Effect in Twin Study

Sillanpää

Ripatti

et al. 2014

Genetic Epidemiology

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“…Associated with increased levels of LDL-c and total cholesterol [39], metabolic syndrome [40] and blood glucose levels [41]. rs1799837 APOA1 0.01 (T) Associated with high triglycerides and insulin levels after a high-carbohydrate diet [42].…”

Section: Discussionmentioning

confidence: 99%

“…Associated with increased levels of LDL-c and total cholesterol [39], metabolic syndrome [40] and blood glucose levels [41].…”

Section: Bioinformatic Analysis: Rs3813627 Is Likely To Affect Bindinmentioning

confidence: 99%

Association between the APOA2 rs3813627 Single Nucleotide Polymorphism and HDL and APOA1 Levels Through BMI

et al. 2020

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Background: The interaction between obesity and genetic traits on high density lipoprotein (HDL) levels has been extensively studied. The variance of serum HDL has a strong genetic heritability, although the studied variant only explains a small part of this variation. The goal of this study was to investigate the associations between the apolipoprotein type 2 (APOA2) rs3813627 single nucleotide polymorphism (SNP) and anthropometric and biochemical variables, though body mass index (BMI). Methods: This study included 153 subjects (91 overweight/obese (BMI ≥ 25 kg/m2) and 62 non-obese individuals (BMI < 25 kg/m2)). The APOA2 rs3813627 SNP was selected and genotyped. Genotype analysis was performed to analyze the associations between APOA2 SNPs and anthropometric and biochemical variables through BMI. Results: The APOA2 rs3813627 TT genotype was associated with low HDL levels in comparison with the APOA2 rs3813627 GG and GT genotype in overweight/obese individuals, but not in the non-obese subjects (p < 0.05). The same trend was observed in the apolipoprotein type 1 (APOA1) protein levels (p < 0.05). Correlation analysis revealed a negative correlation between HDL and APOA1 levels and APOA2 rs3813627 SNP under recessive model (p < 0.05). The odds ratio for low HDL levels was 3.76 and 3.94 for low APOA1 levels. The mediation analysis of APOA2 rs3813627 SNP through BMI showed a full mediation on HDL and partial mediation on APOA1 levels (p < 0.05). Bioinformatic analysis showed that rs3813627 lies in the APOA2 promoter and overlaps motifs for several bound transcription factors. Conclusions: On the basis of these data, the APOA2 rs3813627 SNP is associated with low HDL and APOA1 levels susceptibility, and this effect was mediated by an increased BMI.

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“…Genomic DNA was isolated from whole blood cells anticoagulated with EDTA using a "salting-out" procedure (26). Polymerase chain reaction (PCR) was used to amplify the fragment of 433 bp at the 5' end of the apoAI gene.…”

Section: Dna Isolation and Genotypingmentioning

confidence: 99%

Association Between MspI Polymorphisms of the Apolipoprotein A-I Gene and Hyperlipidemia in an Iranian Population

Pakdel

Eidgahi

Bandegi

2018

Middle East J Rehabil Health Stud

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Background: One of the most important metabolic disorders is hyperlipidemia. ApoAI protein plays an important role in lipoprotein metabolism. In this study, the association between MspI polymorphisms in the promoter (G-75A) and first intron (C83T) of the apoAI gene and hyperlipidemia was investigated in Semnan, Iran. Methods: A total of 151 unrelated subjects were divided into two groups: the hyperlipidemic (N = 75) and control (N = 76) groups. Genotyping was carried out by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). Results: In the hyperlipidemic group, the frequency of the (+-) variant of the MspI (C83T) locus was higher than that in the control group (P < 0.05). Significant differences were found in serum HDL-C and apoAI levels between different genotypes of MspI (C83T) (P < 0.001 and P = 0.02, respectively). In the hyperlipidemic group, the odds ratios for the (+-) and (-) genotypes of the MspI (C83T) locus in comparison to that for the (++) genotype were 0.26 (P= 0.023) and 3.62 (P = 0.254), respectively. The allelic frequency at the (G-75A) locus was not significantly different in the hyperlipidemic and control groups (P = 0.36). The serum levels of lipid and lipoprotein were not significantly different for all genotypes of MspI (G-75A). The AA/++ and GG/-haplotypes had the lowest and

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Re-sequencing of the APOAI promoter region and the genetic association of the -75G > A polymorphism with increased cholesterol and low density lipoprotein levels among a sample of the Kuwaiti population

Cited by 16 publications

References 51 publications

Bayesian Latent Variable Collapsing Model for Detecting Rare Variant Interaction Effect in Twin Study

Bayesian Latent Variable Collapsing Model for Detecting Rare Variant Interaction Effect in Twin Study

Association between the APOA2 rs3813627 Single Nucleotide Polymorphism and HDL and APOA1 Levels Through BMI

Association Between MspI Polymorphisms of the Apolipoprotein A-I Gene and Hyperlipidemia in an Iranian Population

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