scholarly journals The mouse QTL map helps interpret human genome-wide association studies for HDL cholesterol

2011 ◽  
Vol 52 (6) ◽  
pp. 1139-1149 ◽  
Author(s):  
Magalie S. Leduc ◽  
Malcolm Lyons ◽  
Katayoon Darvishi ◽  
Kenneth Walsh ◽  
Susan Sheehan ◽  
...  
Keyword(s):  
Human Genome ◽  
Association Studies ◽  
Hdl Cholesterol ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Qtl Map

Identification of six novel susceptibility loci for dyslipidemia by longitudinal exome-wide association studies in Japanese

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
M Oguri ◽  
K Kato ◽  
H Horibe ◽  
T Fujimaki ◽  
J Sakuma ◽  
...  
Keyword(s):  
Serum Lipid ◽  
Ldl Cholesterol ◽  
Association Studies ◽  
Density Lipoprotein ◽  
Hdl Cholesterol ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Susceptibility Loci ◽  
Cross Sectional ◽  
Genome Wide

Abstract Background The circulating concentrations of triglycerides, high density lipoprotein (HDL)-cholesterol, and low density lipoprotein (LDL)-cholesterol have a substantial genetic component. Although previous genome-wide association studies identified various genes and loci related to plasma lipid levels, those studies were conducted in a cross-sectional manner. Purpose The purpose of the study was to identify genetic variants that confer susceptibility to hypertriglyceridemia, hypo-HDL-cholesterolemia, and hyper-LDL-cholesterolemia in Japanese. We have now performed longitudinal exome-wide association studies (EWASs) to identify novel loci for dyslipidemia by examining temporal changes in serum lipid profiles. Methods Longitudinal EWASs (mean follow-up period, 5 years) for hypertriglyceridemia (2056 case, 3966 controls), hypo-HDL-cholesterolemia (698 cases, 5324 controls), and hyper-LDL-cholesterolemia (2769 cases, 3251 controls) were performed with Illumina Human Exome arrays. The relation of genotypes of 24,691 single nucleotide polymorphisms (SNPs) that passed quality control to dyslipidemia-related traits was examined with the generalized estimating equation (GEE). To compensate for multiple comparisons of genotypes with each of the three conditions, we applied Bonferroni's correction for statistical significance of association. Replication studies with cross-sectional data were performed for hypertriglyceridemia (2685 cases, 4703 controls), hypo-HDL-cholesterolemia (1947 cases, 6146 controls), and hyper-LDL-cholesterolemia (1719 cases, 5833 controls). Results Longitudinal EWASs revealed that 30 SNPs were significantly (P<2.03 × 10–6 by GEE) associated with hypertriglyceridemia, 46 SNPs with hypo-HDL-cholesterolemia, and 25 SNPs with hyper-LDL-cholesterolemia. After examination of the relation of identified SNPs to serum lipid profiles, linkage disequilibrium, and results of the previous genome-wide association studies, we newly identified rs74416240 of TCHP, rs925368 of GIT2, rs7969300 of ATXN2, and rs12231744 of NAA25 as a susceptibility loci for hypo-HDL-cholesterolemia; and rs34902660 of SLC17A3 and rs1042127 of CDSN for hyper-LDL-cholesterolemia. These SNPs were not in linkage disequilibrium with those previously reported to be associated with dyslipidemia, indicating independent effects of the SNPs identified in the present study on serum concentrations of HDL-cholesterol or LDL-cholesterol in Japanese. According to allele frequency data from the 1000 Genomes project database, five of the six identified SNPs were monomorphic or rare variants in European populations. In the replication study, all six SNPs were associated with dyslipidemia-related phenotypes. Conclusion We have thus identified six novel loci that confer susceptibility to hypo-HDL-cholesterolemia or hyper-LDL-cholesterolemia. Determination of genotypes for these SNPs at these loci may prove informative for assessment of the genetic risk for dyslipidemia in Japanese. Funding Acknowledgement Type of funding source: None

Detecting Epistasis by LASSO-Penalized-Model Search Algorithm in Human Genome-Wide Association Studies

2014 ◽  
Vol 989-994 ◽  
pp. 2426-2430
Author(s):  
Zhi Hui Zhou ◽  
Gui Xia Liu ◽  
Ling Tao Su ◽  
Liang Han ◽  
Lun Yan
Keyword(s):  
Human Genome ◽  
Search Algorithm ◽  
Association Studies ◽  
Simulated Data ◽  
Penalized Regression ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Model Search ◽  
Number Of Factors ◽  
Genome Wide

Extensive studies have shown that many complex diseases are influenced by interaction of certain genes, while due to the limitations and drawbacks of adopting logistic regression (LR) to detect epistasis in human Genome-Wide Association Studies (GWAS), we propose a new method named LASSO-penalized-model search algorithm (LPMA) by restricting it to a tuning constant and combining it with a penalization of the L1-norm of the complexity parameter, and it is implemented utilizing the idea of multi-step strategy. LASSO penalized regression particularly shows advantageous properties when the number of factors far exceeds the number of samples. We compare the performance of LPMA with its competitors. Through simulated data experiments, LPMA performs better regarding to the identification of epistasis and prediction accuracy.

scholarly journals Approximately independent linkage disequilibrium blocks in human populations

2015 ◽  
Author(s):  
Tomaz Berisa ◽  
Joseph K. Pickrell
Keyword(s):  
Linkage Disequilibrium ◽  
Human Genome ◽  
Association Studies ◽  
Automated Analysis ◽  
Genome Wide Association ◽  
Human Populations ◽  
Genome Wide Association Studies ◽  
Multiple Genome ◽  
Genome Wide

We present a method to identify approximately independent blocks of linkage disequilibrium (LD) in the human genome. These blocks enable automated analysis of multiple genome-wide association studies.

scholarly journals Genome-Wide Association Study Reveals First Locus for Anorexia Nervosa and Metabolic Correlations

2016 ◽  
Author(s):  
E. L. Duncan ◽  
L. M. Thornton ◽  
A. Hinney ◽  
M. J. Daly ◽  
P. F. Sullivan ◽  
...  
Keyword(s):  
Anorexia Nervosa ◽  
Genome Wide Association Study ◽  
Association Studies ◽  
Genetic Correlations ◽  
Twin Studies ◽  
Hdl Cholesterol ◽  
Genome Wide Association ◽  
High Morbidity ◽  
Genome Wide Association Studies ◽  
Genome Wide

AbstractAnorexia nervosa (AN) is a serious eating disorder characterized by restriction of energy intake relative to requirements, resulting in abnormally low body weight. It has a lifetime prevalence of approximately 1%, disproportionately affects females1,2, and has no well replicated evidence of effective pharmacological or psychological treatments despite high morbidity and mortality2. Twin studies support a genetic basis for the observed aggregation of AN in families3, with heritability estimates of 48%-74%4. Although initial genome-wide association studies (GWASs) were underpowered5,6, evidence suggested that signals for AN would be detected with increased power5. We present a GWAS of 3,495 AN cases and 10,982 controls with one genome-wide significant locus (index variant rs4622308, p=4.3x10−9) in a region (chr12:56,372,585-56,482,185) which includes six genes. The SNP-chip heritability of AN from these data is 0.20 (SE=0.02), suggesting that a substantial fraction of the twin-based heritability stems from common genetic variation. Using these GWAS results, we also find significant positive genetic correlations with schizophrenia, neuroticism, educational attainment, and HDL cholesterol, and significant negative genetic correlations with body mass, insulin, glucose, and lipid phenotypes. Our results support the reconceptualization of AN as a disorder with both psychiatric and metabolic components.

scholarly journals Meta-analysis of genome-wide association studies of HDL cholesterol response to statins

2016 ◽  
Vol 53 (12) ◽  
pp. 835-845 ◽  
Author(s):  
Iris Postmus ◽  
Helen R Warren ◽  
Stella Trompet ◽  
Benoit J Arsenault ◽  
Christy L Avery ◽  
...  
Keyword(s):  
Association Studies ◽  
Meta Analysis ◽  
Hdl Cholesterol ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide
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