Novel rare alleles of ABCA1 are exclusively associated with extreme high-density lipoprotein-cholesterol levels among the Han Chinese

Hu, Su-Wei; YanFang, Zhong; Hao, Yuantao; Luo, Meiling; Zhou, Yan; Guo, Hui; Wei-jiao, Liao; Wan, Desheng; Wei, Haiyun; Gao, Yueting; Shan, Jinglan; Hu, Bin; Hultén, Maj; Wang, Yiming

doi:10.1515/cclm.2009.284

Cited by 11 publications

(6 citation statements)

References 21 publications

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“…Sampling individuals with extreme phenotypes can enrich the frequency of rare variants and therefore lead to an increase in power compared to random sampling. Recently, several statistical methods have been proposed for rare variants association study when extreme phenotypes are sampled [ 25 , 26 , 27 , 28 , 29 ]. Here, we use random sampling and extreme phenotype sampling, and compare the powers of different methods by the two sample techniques in the same sample size.…”

Section: Introductionmentioning

confidence: 99%

Detecting the Common and Individual Effects of Rare Variants on Quantitative Traits by Using Extreme Phenotype Sampling

Zhou

Wang

Chen

2016

Genes

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Next-generation sequencing technology has made it possible to detect rare genetic variants associated with complex human traits. In recent literature, various methods specifically designed for rare variants are proposed. These tests can be broadly classified into burden and nonburden tests. In this paper, we take advantage of the burden and nonburden tests, and consider the common effect and the individual deviations from the common effect. To achieve robustness, we use two methods of combining p-values, Fisher’s method and the minimum-p method. In rare variant association studies, to improve the power of the tests, we explore the advantage of the extreme phenotype sampling. At first, we dichotomize the continuous phenotypes before analysis, and the two extremes are treated as two different groups representing a dichotomous phenotype. We next compare the powers of several methods based on extreme phenotype sampling and random sampling. Extensive simulation studies show that our proposed methods by using extreme phenotype sampling are the most powerful or very close to the most powerful one in various settings of true models when the same sample size is used.

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Section: Introductionmentioning

confidence: 99%

Detecting the Common and Individual Effects of Rare Variants on Quantitative Traits by Using Extreme Phenotype Sampling

Zhou

Wang

Chen

2016

Genes

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“…This problem can be alleviated through the development of powerful study designs. To this objective, numerous association studies have chosen to sample subjects with extreme phenotypes in the hope of increasing power to detect causal single nucleotide polymorphisms (SNPs) [Clement et al., ; Gu et al., ; Hu et al., ; Khor and Goh, ; Li and Leal, ; Liang et al., ; Price et al., ; Risch and Zhang, ]. There have also been numerous developments in methodology to detect QTLs under these extreme phenotype sampling (EPS) study designs [Chen et al., ; Huang and Lin, ; Li et al., ; Slatkin, ; Wallace et al., ].…”

Section: Introductionmentioning

confidence: 99%

“…In a typical EPS study, the two extremes are treated as two different groups representing a dichotomous phenotype. For example, [Hu et al., ] used the contrast between subjects with high‐density lipoprotein cholesterol (HDL‐C) levels against those with low HDL‐C levels to identify an association with the ABCA1 gene. If the same method of extreme sampling were to instead retain the continuous phenotype values, the gain in information could provide greater power to detect gene‐phenotype associations.…”

Section: Introductionmentioning

confidence: 99%

Detecting Rare Variant Effects Using Extreme Phenotype Sampling in Sequencing Association Studies

Barnett

Lee

Lin

2012

Genetic Epidemiology

123

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In the increasing number of sequencing studies aimed at identifying rare variants associated with complex traits, the power of the test can be improved by guided sampling procedures. We confirm both analytically and numerically that sampling individuals with extreme phenotypes can enrich the presence of causal rare variants and can therefore lead to an increase in power compared to random sampling. While application of traditional rare variant association tests to these extreme phenotype samples requires dichotomizing the continuous phenotypes before analysis, the dichotomization procedure can decrease the power by reducing the information in the phenotypes. To avoid this, we propose a novel statistical method based on optimal SKAT (SKAT-O) that allows us to test for rare variant effects using continuous phenotypes in the analysis of extreme phenotype samples. The increase in power of this method is demonstrated through simulation of a wide range of scenarios as well as in the triglyceride data of the Dallas Heart Study.

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“…Plasma HDL-C concentrations result from the interaction of both genetic and environmental factors such as diet, smoking, alcohol consumption, and physical activity (7)(8)(9)(10)(11)(12)(13)(14). Heritability estimates for HDL-C levels mostly range between 40 and 60% (14) and various genetic polymorphisms of the ABCA1 gene have been associated with HDL-C concentrations in several populations (15)(16)(17)(18). The R230C-ABCA1 gene variant was recently found to be private to the Americas and strongly associated with low HDL-C in Mexican mestizos and Native American populations (19)(20)(21)(22)(23).…”

Section: Introductionmentioning

confidence: 99%

Carbohydrate Intake Modulates the Effect of the ABCA1 -R230C Variant on HDL Cholesterol Concentrations in Premenopausal Women

Romero‐Hidalgo

Villarreal-Molina

González-Barrios

et al. 2012

The Journal of Nutrition

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The R230C variant of the ATP-binding cassette transporter A1 (ABCA1) gene has been consistently associated with decreased HDL-cholesterol (HDL-C) concentrations in several studies in the Mexican mestizo population. However, information on how diet composition modifies the effect of the ABCA1-R230C variant on HDL-C concentrations is very scarce. The aim of the present study was to analyze whether the effect of ABCA1-R230C on HDL-C concentrations is modulated by dietary factors in a nationwide population sample of 3591 adults from the National Health and Nutrition Survey conducted by the State's Employees' Social Security and Social Services Institute. All participants answered a validated questionnaire to assess health status and weekly food consumption. Fasting blood samples were drawn for biochemical analysis and DNA extraction, and the ABCA1-R230C variant was genotyped using TaqMan assays. Statistical analyses consisted of simple linear and multiple regression modeling adjusting for age, BMI, smoking, and alcohol consumption. The overall C risk allele frequency was 9.3% and the variant was significantly associated with low HDL-C concentrations in both sexes. A significant negative correlation between carbohydrate consumption and HDL-C concentrations was observed in women bearing the R230C variant (P = 0.021) and a significant gene-diet interaction was found only in premenopausal women (P = 0.037). In conclusion, the effect of the ABCA1-R230C gene variant on HDL-C concentrations is modulated by carbohydrate intake in premenopausal women. This finding may help design optimized dietary interventions according to sex and ABCA1-R230C genotype.

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Novel rare alleles of ABCA1 are exclusively associated with extreme high-density lipoprotein-cholesterol levels among the Han Chinese

Cited by 11 publications

References 21 publications

Detecting the Common and Individual Effects of Rare Variants on Quantitative Traits by Using Extreme Phenotype Sampling

Detecting the Common and Individual Effects of Rare Variants on Quantitative Traits by Using Extreme Phenotype Sampling

Detecting Rare Variant Effects Using Extreme Phenotype Sampling in Sequencing Association Studies

Carbohydrate Intake Modulates the Effect of the ABCA1 -R230C Variant on HDL Cholesterol Concentrations in Premenopausal Women

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