A Polynesian-specific missense CETP variant alters the lipid profile.

Identifying population-specific genetic variants associated with disease and disease-predisposing traits is important to provide insights into the genetic determinants of health and disease between populations, as well as furthering genomic justice. Various common pan-population polymorphisms at CETP associate with serum lipid profiles and cardiovascular disease. Here, sequencing of CETP identified a missense variant rs1597000001 (p.Pro177Leu) specific to Maori and Pacific people that associates with higher HDL-C and lower LDL-C levels. Each copy of the minor allele associated with higher HDL-C by 0.236 mmol/L and lower LDL-C by 0.133 mmol/L. The rs1597000001 effect on HDL-C is comparable with CETP Mendelian loss-of-function mutations that result in CETP deficiency, consistent with our data, which shows that rs1597000001 lowers CETP activity by 27.9%. This study highlights the potential of population-specific genetic analyses for improving equity in genomics and health outcomes for population groups underrepresented in genomic studies.

Assessment of established HDL-C loci for association with HDL-C levels and type 2 diabetes in Pima Indians.

AIMS/HYPOTHESIS: Epidemiological studies in Pima Indians identified elevated levels of HDL-cholesterol (HDL-C) as a protective factor against type 2 diabetes risk in women. We assessed whether HDL-C-associated single-nucleotide polymorphisms (SNPs) also associate with type 2 diabetes in female Pima Indians. METHODS: Twenty-one SNPs in established HDL-C loci were initially analysed in 2,675 full-heritage Pima Indians. SNPs shown to associate with HDL-C (12 SNPs) were assessed for association with type 2 diabetes in 7,710 Pima Indians (55.6% female sex). The CETP locus provided the strongest evidence for association with HDL-C and was further interrogated by analysing tag SNPs. RESULTS: Twelve of the 21 SNPs analysed had a significant association with HDL-C in Pima Indians; five SNPs representing four loci (CETP, DOCK6, PPP1R3B and ABCA1) reached genome-wide significance. Three SNPs, at CETP, KLF14 and HNF4A, associated with type 2 diabetes only in female participants with the HDL-C-lowering allele increasing diabetes risk (p values: 3.2 × 10(-4) to 7.7 × 10(-5)); the association remained significant even after adjustment for HDL-C. Additional analysis across CETP identified rs6499863 as having the strongest association with type 2 diabetes in female participants (p = 5.0 × 10(-6)) and this association remained independent of the HDL-C association. CONCLUSIONS/INTERPRETATION: SNPs at the CETP, HNF4A and KLF14 locus are associated with HDL-C levels and type 2 diabetes (in female participants). However, since HNF4A and KLF14 are established loci for type 2 diabetes, it is unlikely that HDL-C solely mediates these associations.

Genotype by energy expenditure interaction with metabolic syndrome traits: the Portuguese healthy family study.

Moderate-to-high levels of physical activity are established as preventive factors in metabolic syndrome development. However, there is variability in the phenotypic expression of metabolic syndrome under distinct physical activity conditions. In the present study we applied a Genotype X Environment interaction method to examine the presence of GxEE interaction in the phenotypic expression of metabolic syndrome. A total of 958 subjects, from 294 families of The Portuguese Healthy Family study, were included in the analysis. Total daily energy expenditure was assessed using a 3 day physical activity diary. Six metabolic syndrome related traits, including waist circumference, systolic blood pressure, glucose, HDL cholesterol, total cholesterol and triglycerides, were measured and adjusted for age and sex. GxEE examination was performed on SOLAR 4.3.1. All metabolic syndrome indicators were significantly heritable. The GxEE interaction model fitted the data better than the polygenic model (p<0.001) for waist circumference, systolic blood pressure, glucose, total cholesterol and triglycerides. For waist circumference, glucose, total cholesterol and triglycerides, the significant GxEE interaction was due to rejection of the variance homogeneity hypothesis. For waist circumference and glucose, GxEE was also significant by the rejection of the genetic correlation hypothesis. The results showed that metabolic syndrome traits expression is significantly influenced by the interaction established between total daily energy expenditure and genotypes. Physical activity may be considered an environmental variable that promotes metabolic differences between individuals that are distinctively active.

Prospective assessment of genetic effects on progression to different stages of age-related macular degeneration using multistate Markov models.

PURPOSE: Understanding the effect of genes on progression to different stages of age-related macular degeneration (AMD) may suggest stage-specific therapeutic targets and more precise prediction of the development of this disease. METHODS: Progression events and time to each stage of AMD were derived from the longitudinal data of 2560 subjects without advanced AMD. SNPs in 12 AMD risk loci were genotyped. A multistate Markov model for progression from normal to intermediate drusen, then to large drusen, and eventually to neovascular disease (NV) or geographic atrophy (GA) was applied to estimate stage-specific hazard ratios for each SNP. The effects of these genetic factors were also estimated by a multivariate multistate Markov model adjusted for baseline age, sex, smoking, body mass index (BMI), education, antioxidant treatment, and the status of AMD in the fellow eye. RESULTS: Controlling for demographic and behavioral factors and other SNPs, the TT genotype of rs10468017 in LIPC was associated with decreased risk of progression from large drusen to NV (HR = 0.57, P = 0.04) and tended to reduce the risk of progression from normal to intermediate drusen (HR = 0.72, P = 0.07). The SNP rs1883025 (T allele) in ABCA1 was associated with decreased risk of progression from normal to intermediate drusen (HR per allele = 0.82 per allele, P = 9.7 × 10(-3)) and from intermediate drusen to large drusen (HR per allele = 0.77, P = 5.2 × 10(-3)). The genes CFH, C3, CFB, and ARMS2/HTRA1 were associated with progression from intermediate drusen to large drusen and from large drusen to GA or NV. CONCLUSIONS: Genes in different pathways influence progression to different stages of AMD.

Environmental factors, familial aggregation and heritability of total cholesterol, low density lipoprotein-cholesterol and high density lipoprotein-cholesterol in a Brazilian population assisted by the Family Doctor Program.

OBJECTIVES: To estimate familial aggregation and the heritability of total cholesterol (TC), low density lipoprotein-cholesterol (LDL-C) and high density lipoprotein-cholesterol (HDL-C) in families assisted by the Family Doctor Program in a Brazilian city, and to evaluate associations between some environmental factors and familial aggregation of these lipids. STUDY DESIGN: Cross-sectional familial study. METHODS: The association of lipids with sociodemographic factors, lifestyle factors and comorbidities (e.g. physical activity, alcohol consumption, smoking, hypertension, impaired glucose tolerance, body mass index) was estimated using linear models and generalized estimating equations. Correlation of TC, LDL-C and HDL-C between pairs of relatives was estimated with the familial correlation procedure, and heritability was estimated with the ASSOC procedure. RESULTS: All associations were statistically significant. There was familial aggregation of TC (parent/offspring, r=0.33; sibling/sibling, r=0.37), LDL-C (parent/offspring, r=0.29; sibling/sibling, r=0.37) and HDL-C (parent/offspring, r=0.25; sibling/sibling, r=0.48), but less than 3%, 6% and 14%, respectively, which was explained by lifestyle factors. Correlation between pairs with genetic sharing (parent/offspring and sibling/sibling) was higher than that observed between father and mother. Heritability estimates ranged between 0.32 (HDL-C) and 0.50 (TC). Similar results were found for the two approaches used to estimate the contribution of genetic and environmental factors in the correlation of TC, LDL-C and HDL-C between the family pairs. CONCLUSION: The results showed that there is familial aggregation of TC, LDL-C and HDL-C, and point to the predominance of genetic factors because little influence of environmental variables was found.

Common variants near MC4R in relation to body fat, body fat distribution, metabolic traits and energy expenditure.

OBJECTIVE: Common variants near melanocortin receptor 4 (MC4R) have been related to fatness and type 2 diabetes. We examined the associations of rs17782313 and rs17700633 in relation to body fat, body fat distribution, metabolic traits, weight development and energy expenditure. METHODS: Obese young men (n = 753, BMI > or = 31.0 kg m(-2)) and a randomly selected group (n = 874) identified from a population of 174 800 men were re-examined in three surveys at mean ages 35, 46 and 49 years (S-35, S-46 and S-49). Measurements were available at upto eight times from birth to adulthood. Logistic regression analysis was used to assess odds ratio (OR) for the presence of the carrier allele for a given difference in phenotypic values. RESULTS: Rs17782313 minor C-allele was associated with overall, abdominal and peripheral fatness (range of OR = 1.06-1.14 per z-score units) at all three surveys, although only consistently significant at S-35 and S-46. Rs17700633 minor A-allele was also associated with the fatness measures, but significantly so only at S-49 for overall and abdominal fatness (range of OR = 1.03-1.15 per z-score units), and peripheral fatness (OR = 1.15-1.20 per z-score units). There were only few significant associations with metabolic traits. The rs17782313 C-allele and the rs17700633 A-allele were both associated with lower high-density lipoprotein cholesterol (range of OR = 0.64-0.84 per mol l(-1)), significantly at S-46. The rs17700633 A-allele was significantly associated with insulin (OR = 1.25 per 50 pmol l(-1)), leptin (OR = 1.42 per 10 ng microl(-1)) and insulin sensitivity (OR = 0.81 per model unit). The rs17782313 C-allele and the rs17700633 A-allele were both associated with BMI in childhood and adolescence (range of OR = 1.04-1.17 per z-score units), significant for the rs17782313 C-allele at the age of 13-19 years and for rs17700633 A-allele at age 7, 10, 13 and 19 years. No significant associations were found for energy expenditure. CONCLUSION: Near MC4R variants appear to contribute to body fat, body fat distribution, some metabolic traits, weight development during childhood, but not to energy expenditure.

An experimental assessment of in silico haplotype association mapping in laboratory mice.

BACKGROUND: To assess the utility of haplotype association mapping (HAM) as a quantitative trait locus (QTL) discovery tool, we conducted HAM analyses for red blood cell count (RBC) and high density lipoprotein cholesterol (HDL) in mice. We then experimentally tested each HAM QTL using published crosses or new F2 intercrosses guided by the haplotype at the HAM peaks. RESULTS: The HAM for RBC, using 33 classic inbred lines, revealed 8 QTLs; 2 of these were true positives as shown by published crosses. A HAM-guided (C57BL/6J x CBA/J)F2 intercross we carried out verified 2 more as true positives and 4 as false positives. The HAM for HDL, using 81 strains including recombinant inbred lines and chromosome substitution strains, detected 46 QTLs. Of these, 36 were true positives as shown by published crosses. A HAM-guided (C57BL/6J x A/J)F2 intercross that we carried out verified 2 more as true positives and 8 as false positives. By testing each HAM QTL for RBC and HDL, we demonstrated that 78% of the 54 HAM peaks were true positives and 22% were false positives. Interestingly, all false positives were in significant allelic association with one or more real QTL. CONCLUSION: Because type I errors (false positives) can be detected experimentally, we conclude that HAM is useful for QTL detection and narrowing. We advocate the powerful and economical combined approach demonstrated here: the use of HAM for QTL discovery, followed by mitigation of the false positive problem by testing the HAM-predicted QTLs with small HAM-guided experimental crosses.

Genome-wide linkage scan for plasma high density lipoprotein cholesterol, apolipoprotein A-1 and triglyceride variation among American Indian populations: the Strong Heart Family Study.

BACKGROUND: Recent studies have identified chromosomal regions linked to variation in high density lipoprotein cholesterol (HDL-C), apolipoprotein A-1 (apo A-1) and triglyceride (TG), although results have been inconsistent and previous studies of American Indian populations are limited. OBJECTIVE: In an attempt to localise quantitative trait loci (QTLs) influencing HDL-C, apo A-1 and TG, we conducted genome-wide linkage scans of subjects of the Strong Heart Family Study. METHODS: We implemented analyses in 3484 men and women aged 18 years or older, at three study centres. RESULTS: With adjustment for age, sex and centre, we detected a QTL influencing both HDL-C (logarithm of odds (LOD) = 4.4, genome-wide p = 0.001) and apo A-1 (LOD = 3.2, genome-wide p = 0.020) nearest marker D6S289 at 6p23 in the Arizona sample. Another QTL influencing apo A-1 was found nearest marker D9S287 at 9q22.2 (LOD = 3.0, genome-wide p = 0.033) in the North and South Dakotas. We detected a QTL influencing TG nearest marker D15S153 at 15q22.31 (LOD = 4.5 in the overall sample and LOD = 3.8 in the Dakotas sample, genome-wide p = 0.0044) and when additionally adjusted for waist, current smoking, current alcohol, current oestrogen, lipid treatment, impaired fasting glucose, and diabetes, nearest marker D10S217 at 10q26.2 (LOD = 3.7, genome-wide p = 0.0058) in the Arizona population. CONCLUSIONS: The replication of QTLs in regions of the genome that harbour well known candidate genes suggest that chromosomes 6p, 9q and 15q warrant further investigation with fine mapping for causative polymorphisms in American Indians.

Genetic differences between the determinants of lipid profile phenotypes in African and European Americans: the Jackson Heart Study.

Genome-wide association analysis in populations of European descent has recently found more than a hundred genetic variants affecting risk for common disease. An open question, however, is how relevant the variants discovered in Europeans are to other populations. To address this problem for cardiovascular phenotypes, we studied a cohort of 4,464 African Americans from the Jackson Heart Study (JHS), in whom we genotyped both a panel of 12 recently discovered genetic variants known to predict lipid profile levels in Europeans and a panel of up to 1,447 ancestry informative markers allowing us to determine the African ancestry proportion of each individual at each position in the genome. Focusing on lipid profiles -- HDL-cholesterol (HDL-C), LDL-cholesterol (LDL-C), and triglycerides (TG) -- we identified the lipoprotein lipase (LPL) locus as harboring variants that account for interethnic variation in HDL-C and TG. In particular, we identified a novel common variant within LPL that is strongly associated with TG (p = 2.7 x 10(-6)) and explains nearly 1% of the variability in this phenotype, the most of any variant in African Americans to date. Strikingly, the extensively studied "gain-of-function" S447X mutation at LPL, which has been hypothesized to be the major determinant of the LPL-TG genetic association and is in trials for human gene therapy, has a significantly diminished strength of biological effect when it is found on a background of African rather than European ancestry. These results suggest that there are other, yet undiscovered variants at the locus that are truly causal (and are in linkage disequilibrium with S447X) or that work synergistically with S447X to modulate TG levels. Finally, we find systematically lower effect sizes for the 12 risk variants discovered in European populations on the African local ancestry background in JHS, highlighting the need for caution in the use of genetic variants for risk assessment across different populations.

Low high-density lipoprotein cholesterol: an important consideration in coronary heart disease risk assessment.

PURPOSE OF REVIEW: One aim is to summarize evidence from observational studies and clinical trials evaluating the inverse relationship between high-density lipoprotein and coronary heart disease. Other aims are to explore the mechanisms underlying the reported cardioprotective effects of high-density lipoprotein and to evaluate therapeutic modalities to increase high-density lipoprotein levels and functionality. RECENT FINDINGS: In addition to reverse cholesterol transport, recent data suggest that high-density lipoprotein possesses antioxidant, anti-inflammatory and fibrinolytic properties and the inverse relationship between high-density lipoprotein cholesterol and coronary heart disease is most evident with associated elevations in low-density lipoprotein cholesterol and triglyceride. Recent data suggest, however, that even after low-density lipoprotein cholesterol is sufficiently reduced, residual coronary heart disease risk persists with low high-density lipoprotein cholesterol. The excess death rate reported with the high-density lipoprotein cholesterol raising drug torcetrapib appears to have been the result of an off-target effect of the drug, rather than an effect attributable to cholesteryl ester transfer protein inhibition. SUMMARY: Low high-density lipoprotein cholesterol remains an important consideration in coronary heart disease risk assessment, however several issues remain unresolved. They include the extent to which low high-density lipoprotein cholesterol in the absence of other risk factors augments risk, the relationship between high-density lipoprotein functionality and levels of high-density lipoprotein cholesterol and whether and to what extent improving these parameters independently offsets coronary heart disease risk.

Newly identified loci that influence lipid concentrations and risk of coronary artery disease.

To identify genetic variants influencing plasma lipid concentrations, we first used genotype imputation and meta-analysis to combine three genome-wide scans totaling 8,816 individuals and comprising 6,068 individuals specific to our study (1,874 individuals from the FUSION study of type 2 diabetes and 4,184 individuals from the SardiNIA study of aging-associated variables) and 2,758 individuals from the Diabetes Genetics Initiative, reported in a companion study in this issue. We subsequently examined promising signals in 11,569 additional individuals. Overall, we identify strongly associated variants in eleven loci previously implicated in lipid metabolism (ABCA1, the APOA5-APOA4-APOC3-APOA1 and APOE-APOC clusters, APOB, CETP, GCKR, LDLR, LPL, LIPC, LIPG and PCSK9) and also in several newly identified loci (near MVK-MMAB and GALNT2, with variants primarily associated with high-density lipoprotein (HDL) cholesterol; near SORT1, with variants primarily associated with low-density lipoprotein (LDL) cholesterol; near TRIB1, MLXIPL and ANGPTL3, with variants primarily associated with triglycerides; and a locus encompassing several genes near NCAN, with variants strongly associated with both triglycerides and LDL cholesterol). Notably, the 11 independent variants associated with increased LDL cholesterol concentrations in our study also showed increased frequency in a sample of coronary artery disease cases versus controls.

Genome scan for quantitative trait loci influencing HDL levels: evidence for multilocus inheritance in familial combined hyperlipidemia.

Several genome scans in search of high-density lipoprotein (HDL) quantitative trait loci (QTLs) have been performed. However, to date the actual identification of genes implicated in the regulation of common forms of HDL abnormalities remains unsuccessful. This may be due, in part, to the oligogenic and multivariate nature of HDL regulation, and potentially, pleiotropy affecting HDL and other lipid-related traits. Using a Bayesian Markov Chain Monte Carlo (MCMC) approach, we recently provided evidence of linkage of HDL level variation to the APOA1-C3-A4-A5 gene complex, in familial combined hyperlipidemia pedigrees, with an estimated number of two to three large QTLs remaining to be identified. We also presented results consistent with pleiotropy affecting HDL and triglycerides at the APOA1-C3-A4-A5 gene complex. Here we use the same MCMC analytic strategy, which allows for oligogenic trait models, as well as simultaneous incorporation of covariates, in the context of multipoint analysis. We now present results from a genome scan in search for the additional HDL QTLs in these pedigrees. We provide evidence of linkage for additional HDL QTLs on chromosomes 3p14 and 13q32, with results on chromosome 3 further supported by maximum parametric and variance component LOD scores of 3.0 and 2.6, respectively. Weaker evidence of linkage was also obtained for 7q32, 12q12, 14q31-32 and 16q23-24.

Heritability estimates from human twin data by incorporating historical prior information.

Bayesian methods are commonly used in some analyses of human genetic data, such as segregation and linkage analyses, but they are not typically used for analyses of human twin data. In this paper we develop a scheme for a Bayesian analysis of human twin data. We develop prior elicitation schemes to incorporate historical information. We consider three prior schemes: fully informative, semi-informative and noninformative. We use Markov chain Monte Carlo sampling algorithms to facilitate Bayesian computation and provide detailed implementation schemes. We also develop model diagnostics for assessing the goodness of fit of twin models. Using a simulation study, we show that if the purpose of the study is to estimate the intraclass correlations or heritability in twin studies, then the semi-informative prior is as informative as the fully informative prior. Finally, a real data example is used to illustrate the proposed methodologies.

Genetic and environmental covariance of serum cholesterol and blood pressure in female twins.

Blood pressure elevation is frequently associated with elevated cholesterol, triglyceride or low density lipoprotein (LDL-C) or low high density lipoprotein (HDL-C). The relative importance of genetic and environmental factors in these associations is unclear. We examined the relative contribution of genetic and environmental influences to the association between blood pressure and serum lipids in 75 pairs of female twins using path analysis and maximum-likelihood model fitting. Associations between systolic blood pressure and total cholesterol (r = 0.44, P < 0.001), and LDL-C (r = 0.38, P < 0.001), but not HDL-C (r = 0.05, N.S.), remained significant after age and body mass index adjustment. Univariate models suggested genetic effects contributed 60-70% to the variance of total cholesterol, LDL-C, HDL-C and systolic blood pressure. The remaining variance was explained by age and/or unique environmental influences. Using bivariate models, we demonstrated genetic (P = 0.017) and unique environmental covariance (P = 0.011) of cholesterol and systolic blood pressure. Significant genetic covariance (P = 0.038) was observed between LDL-C and systolic blood pressure. The association between blood pressure and total cholesterol in these twins results from shared genetic and similar unique environmental influences. The association between LDL-C and blood pressure is partly due to shared genetic influences. We conclude that both additive genetic and environmental factors unique to the individual are important determinants of the relationships between serum lipids and blood pressure.

A bivariate genetic analysis of HDL- and LDL-cholesterol incorporating measured covariates: a Gibbs sampling application.

We analyzed HDL- and LDL-cholesterol levels as a bivariate phenotype in 27 families as a function of major genes, polygenes, and measured covariates using a Monte Carlo sampling technique called Gibbs sampling. Major genes and polygenes exhibited strong effects, when considered separately. While a major gene versus polygene model could not be clearly differentiated for HDL-C, polygenes appeared to play a stronger role than a major gene for LDL-C. There was no evidence of linkage between the two major genes for HDL- and LDL-C, and the correlation in polygenes was negative. The analysis illustrate the potential applicability of Gibbs sampling to such complex problems as the multivariate analysis of continuous phenotypes.