Genetic determinants of obesity-related lipid traits

Genetic architecture of lipid traits changes over time and differs by race: Princeton Lipid Follow-up Study

Dyslipidemia is a major risk factor for CVD. Previous studies on lipid heritability have largely focused on white populations assessed after the obesity epidemic. Given secular trends and racial differences in lipid levels, this study explored whether lipid heritability is consistent across time and between races. African American and white nuclear families had fasting lipids measured in the 1970s and 22-30 years later. Heritability was estimated, and bivariate analyses between visits were conducted by race using variance components analysis. A total of 1,454 individuals (age 14.1/40.6 for offspring/parents at baseline; 39.6/66.5 at follow-up) in 373 families (286 white, 87 African American) were included. Lipid trait heritabilities were typically stronger during the 1970s than the 2000s. At baseline, additive genetic variation for LDL was significantly lower in African Americans than whites (P = 0.015). Shared genetic contribution to lipid variability over time was significant in both whites (all P < 0.0001) and African Americans (P ≤ 0.05 for total, LDL, and HDL cholesterol). African American families demonstrated shared environmental contributions to lipid variation over time (all P ≤ 0.05). Lower heritability, lower LDL genetic variance, and durable environmental effects across the obesity epidemic in African American families suggest race-specific approaches are needed to clarify the genetic etiology of lipids.

A novel method, the Variant Impact On Linkage Effect Test (VIOLET), leads to improved identification of causal variants in linkage regions

The Human Genome Project was expected to individualize medicine by rapidly advancing knowledge of common complex disease through discovery of disease-causing genetic variants. However, this has proved challenging. Although linkage analysis has identified replicated chromosomal regions, subsequent detection of causal variants for complex traits has been limited. One explanation for this difficulty is that utilization of association to follow up linkage is problematic given that linkage and association are not required to co-occur. Indeed, co-occurrence is likely to occur only in special circumstances, such as Mendelian inheritance, but cannot be universally expected. To overcome this problem, we propose a novel method, the Variant Impact On Linkage Effect Test (VIOLET), which differs from other quantitative methods in that it is designed to follow up linkage by identifying variants that influence the variance explained by a quantitative trait locus. VIOLET's performance was compared with measured genotype and combined linkage association in two data sets with quantitative traits. Using simulated data, VIOLET had high power to detect the causal variant and reduced false positives compared with standard methods. Using real data, VIOLET identified a single variant, which explained 24% of linkage; this variant exhibited only nominal association (P=0.04) using measured genotype and was not identified by combined linkage association. These results demonstrate that VIOLET is highly specific while retaining low false-negative results. In summary, VIOLET overcomes a barrier to gene discovery and thus may be broadly applicable to identify underlying genetic etiology for traits exhibiting linkage.

A comprehensive analysis of adiponectin QTLs using SNP association, SNP cis-effects on peripheral blood gene expression and gene expression correlation identified novel metabolic syndrome (MetS) genes with potential role in carcinogenesis and systemic inflammation

BACKGROUND

Metabolic syndrome (MetS) is an aberration associated with increased risk for cancer and inflammation. Adiponectin, an adipocyte-produced abundant protein hormone, has countering effect on the diabetogenic and atherogenic components of MetS. Plasma levels of adiponectin are negatively correlated with onset of cancer and cancer patient mortality. We previously performed microsatellite linkage analyses using adiponectin as a surrogate marker and revealed two QTLs on chr5 (5p14) and chr14 (14q13).

METHODS

Using individuals from 85 extended families that contributed to the linkage and who were measured for 42 clinical and biologic MetS phenotypes, we tested QTL-based SNP associations, peripheral white blood cell (PWBC) gene expression, and the effects of cis-acting SNPs on gene expression to discover genomic elements that could affect the pathophysiology and complications of MetS.

RESULTS

Adiponectin levels were found to be highly intercorrelated phenotypically with the majority of MetS traits. QTL-specific haplotype-tagging SNPs associated with MetS phenotypes were annotated to 14 genes whose function could influence MetS biology as well as oncogenesis or inflammation. These were mechanistically categorized into four groups: cell-cell adhesion and mobility, signal transduction, transcription and protein sorting. Four genes were highly prioritized: cadherin 18 (CDH18), myosin X (MYO10), anchor protein 6 of AMPK (AKAP6), and neuronal PAS domain protein 3 (NPAS3). PWBC expression was detectable only for the following genes with multi-organ or with multi-function properties: NPAS3, MARCH6, MYO10 and FBXL7. Strong evidence of cis-effects on the expression of MYO10 in PWBC was found with SNPs clustered near the gene's transcription start site. MYO10 expression in PWBC was marginally correlated with body composition (p = 0.065) and adipokine levels in the periphery (p = 0.064). Variants of genes AKAP6, NPAS3, MARCH6 and FBXL7 have been previously reported to be associated with insulin resistance, inflammatory markers or adiposity studies using genome-wide approaches whereas associations of CDH18 and MYO10 with MetS traits have not been reported before.

CONCLUSIONS

Adiponectin QTLs-based SNP association and mRNA expression identified genes that could mediate the association between MetS and cancer or inflammation.

Haplotype combination of the bovine INSIG1 gene sequence variants and association with growth traits in Nanyang cattle

The insulin-induced gene 1 (INSIG1) gene encodes a protein that blocks proteolytic activation of sterol regulatory element binding proteins, which are transcription factors that activate genes that regulate cholesterol, fatty acid, and glucose metabolism. However, similar research for the bovine INSIG1 gene is lacking. Therefore, in this study, polymorphisms of the bovine INSIG1 gene were detected in 643 individuals from four cattle breeds by DNA pooling, forced PCR-RFLP, PCR-SSCP, and DNA sequencing methods. Only 10 novel SNPs were identified, which included four mutations in the coding region and the others in the introns. In Nanyang individuals, seven common haplotypes were identified based on four coding region SNPs. The haplotype GACT, with a frequency of 75.4%, was the most prevalent haplotypes and SNPs formed two linkage disequilibrium blocks with strong multi-allelic D' (D' = 1). Additionally, association analysis between mutations of the bovine INSIG1 gene and growth traits in Nanyang cattle at 6, 12, 18, and 24 months old was performed, and the results indicated that the polymorphisms were not significantly associated with body mass.

Accounting for a quantitative trait locus for plasma triglyceride levels: utilization of variants in multiple genes

Background

For decades, research efforts have tried to uncover the underlying genetic basis of human susceptibility to a variety of diseases. Linkage studies have resulted in highly replicated findings and helped identify quantitative trait loci (QTL) for many complex traits; however identification of specific alleles accounting for linkage remains elusive. The purpose of this study was to determine whether with a sufficient number of variants a linkage signal can be fully explained.

Method

We used comprehensive fine-mapping using a dense set of single nucleotide polymorphisms (SNPs) across the entire quantitative trait locus (QTL) on human chromosome 7q36 linked to plasma triglyceride levels. Analyses included measured genotype and combined linkage association analyses.

Results

Screening this linkage region, we found an over representation of nominally significant associations in five genes (MLL3, DPP6, PAXIP1, HTR5A, INSIG1). However, no single genetic variant was sufficient to account for the linkage. On the other hand, multiple variants capturing the variation in these five genes did account for the linkage at this locus. Permutation analyses suggested that this reduction in LOD score was unlikely to have occurred by chance (p = 0.008).

Discussion

With recent findings, it has become clear that most complex traits are influenced by a large number of genetic variants each contributing only a small percentage to the overall phenotype. We found that with a sufficient number of variants, the linkage can be fully explained. The results from this analysis suggest that perhaps the failure to identify causal variants for linkage peaks may be due to multiple variants under the linkage peak with small individual effect, rather than a single variant of large effect.

A two-step genetic study on quantitative precursors of coronary artery disease in a homogeneous Indian population: case-control association discovery and validation by transmission-disequilibrium test

In spite of its strong familiality, gene identification for coronary artery disease (CAD) has not yielded a consistent picture. One major reason for this is that families or cases and controls were not recruited from a homogeneous population. We, therefore, attempted to map genes underlying 10 quantitative traits (QTs) that are known precursors of CAD in a homogeneous population (Marwari) of India. The QTs are apolipoprotein B (ApoB), C-reactive protein (CRP), fibrinogen (FBG), homocysteine (HCY), lipoprotein (a) (LPA), cholesterol - total (CHOL-T), cholesterol - HDL (CHOL-H), cholesterol - LDL (CHOL-L), cholesterol - VLDL (CHOL-V) and triglyceride (TG). We assayed 209 SNPs in 31 genes among members of Marwari families. After log-transformation and covariate-adjustment of the QTs, a two-step analysis was performed. In Step-1, data on unrelated individuals were analysed for association with the SNPs. In Step-2, for validation of Step-1 results, a quantitative transmission-disequilibrium test on parent- offspring data was performed for each SNP found to be significantly associated with a QT in Step-1 on an independent sample set drawn from the same population. Statistically significant results found for the various QTs and SNPs were: rs3774933, rs230528, rs230521, rs1005819 and rs1609798 (intronic, NFKB1) with APOB; rs5361 (Missense, R greatr than S, SELE) and rs4648004 (Intronic, NFKB1) with FBG; rs4220 (Missense, K greater than R, FGB) with HCY; and rs3025035 (Intronic, VEGFA) with CHOL-H. SNPs in SELE, VEGFA, FGB and NFKB1 genes impact significantly on levels of quantitative precursors of CAD in Marwaris.

Detection of quantitative trait loci affecting serum cholesterol, LDL, HDL, and triglyceride in pigs

Background

Serum lipids are associated with many serious cardiovascular diseases and obesity problems. Many quantitative trait loci (QTL) have been reported in the pig mostly for performance traits but very few for the serum lipid traits. In contrast, remarkable numbers of QTL are mapped for serum lipids in humans and mice. Therefore, the objective of this research was to investigate the chromosomal regions influencing the serum level of the total cholesterol (CT), triglyceride (TG), high density protein cholesterol (HDL) and low density protein cholesterol (LDL) in pigs. For this purpose, a total of 330 animals from a Duroc × Pietrain F2 resource population were phenotyped for serum lipids using ELISA and were genotyped by using 122 microsatellite markers covering all porcine autosomes for QTL study in QTL Express. Blood sampling was performed at approximately 175 days before slaughter of the pig.

Results

Most of the traits were correlated with each other and were influenced by average daily gain, slaughter date and age. A total of 18 QTL including three QTL with imprinting effect were identified on 11 different porcine autosomes. Most of the QTL reached to 5% chromosome-wide (CW) level significance including a QTL at 5% experiment-wide (GW) and a QTL at 1% GW level significance. Of these QTL four were identified for both the CT and LDL and two QTL were identified for both the TG and LDL. Moreover, three chromosomal regions were detected for the HDL/LDL ratio in this study. One QTL for HDL on SSC2 and two QTL for TG on SSC11 and 17 were detected with imprinting effect. The highly significant QTL (1% GW) was detected for LDL at 82 cM on SSC1, whereas significant QTL (5% GW) was identified for HDL/LDL on SSC1 at 87 cM. Chromosomal regions with pleiotropic effects were detected for correlated traits on SSC1, 7 and 12. Most of the QTL identified for serum lipid traits correspond with the previously reported QTL for similar traits in other mammals. Two novel QTL on SSC16 for HDL and HDL/LDL ratio and an imprinted QTL on SSS17 for TG were detected in the pig for the first time.

Conclusion

The newly identified QTL are potentially involved in lipid metabolism. The results of this work shed new light on the genetic background of serum lipid concentrations and these findings will be helpful to identify candidate genes in these QTL regions related to lipid metabolism and serum lipid concentrations in pigs.

Quantification of the clinical modifiers impacting high-density lipoprotein cholesterol in the community: Personalized Medicine Research Project

High-density lipoprotein (HDL) cholesterol levels are inversely correlated with the development of cardiovascular disease. To date, genetic association studies have explained only a small proportion of the overall variance in HDL cholesterol. Further studies are needed, within practice-based cohorts, to place genetic findings into context alongside important clinical variables (eg, age, sex, body mass index, medication use, and clinical comorbidity). The Marshfield Clinic Personalized Medicine Research Project database was designed for large-scale studies of genetic epidemiology in a clinical practice-based setting. Because of its size and its unique practice-based design, this resource will provide adequate statistical power for the assessment of genetic findings related to HDL cholesterol level within the context of covariates known to modify lipid homeostasis. The authors report construction and validation of novel electronic phenotyping algorithms that can be used to model individual baseline HDL cholesterol levels within this practice-based resource. Because these algorithms were developed in a setting that reflects routine clinical care, future genetic studies using these algorithms within practice-based DNA biobanks should facilitate the identification of markers with optimal effect size after adjustment for known clinical factors contributing to the overall variance in HDL cholesterol level within the community.

Univariate and bivariate linkage analysis identifies pleiotropic loci underlying lipid levels and type 2 diabetes risk

Dyslipidemia frequently co-occurs with type 2 diabetes (T2D) and with obesity. To investigate whether the co-occurrence is due to pleiotropic genes, we performed univariate linkage analysis of lipid levels and bivariate linkage analysis of pairs of lipid levels and of lipid levels paired with T2D, body mass index (BMI), and waist-hip ratio (WHR) in the African American subset of the Genetics of NIDDM (GENNID) sample. We obtained significant evidence for a pleiotropic low density lipoprotein cholesterol (LDL-C)-T2D locus on chromosome 1 at 16-19 megabases (MB) (bivariate lod = 4.41), as well as a non-pleiotropic triglyceride (TG) locus on chromosome 20 at 28-34 MB (univariate lod = 3.57). In addition, near-significant evidence supported TG-T2D loci on chromosome 2 at 81-101 MB (bivariate lod = 4.23) and 232-239 MB (bivariate lod = 4.27) and on chromosome 7 at 147-151 MB (univariate lod = 3.08 for TG with P = 0.041 supporting pleiotropy with T2D), as well as an LDL-C-BMI locus on chromosome 3 at 137-147 MB (bivariate lod score = 4.25). These findings provide evidence that at least some of the co-occurrence of dyslipidemia with T2D and obesity is due to common underlying genes.

Serotonin (5-HT) receptor 5A sequence variants affect human plasma triglyceride levels

Neurotransmitters such as serotonin (5-hydroxytryptamine, 5-HT) work closely with leptin and insulin to fine-tune the metabolic and neuroendocrine responses to dietary intake. Losing the sensitivity to excess food intake can lead to obesity, diabetes, and a multitude of behavioral disorders. It is largely unclear how different serotonin receptor subtypes respond to and integrate metabolic signals and which genetic variations in these receptor genes lead to individual differences in susceptibility to metabolic disorders. In an obese cohort of families of Northern European descent (n = 2,209), the serotonin type 5A receptor gene, HTR5A, was identified as a prominent factor affecting plasma levels of triglycerides (TG), supported by our data from both genome-wide linkage and targeted association analyses using 28 publicly available and 12 newly discovered single nucleotide polymorphisms (SNPs), of which 3 were strongly associated with plasma TG levels (P < 0.00125). Bayesian quantitative trait nucleotide (BQTN) analysis identified a putative causal promoter SNP (rs3734967) with substantial posterior probability (P = 0.59). Functional analysis of rs3734967 by electrophoretic mobility shift assay (EMSA) showed distinct binding patterns of the two alleles of this SNP with nuclear proteins from glioma cell lines. In conclusion, sequence variants in HTR5A are strongly associated with high plasma levels of TG in a Northern European population, suggesting a novel role of the serotonin receptor system in humans. This suggests a potential brain-specific regulation of plasma TG levels, possibly by alteration of the expression of HTR5A.

INSIG1 influences obesity-related hypertriglyceridemia in humans

In our analysis of a quantitative trait locus (QTL) for plasma triglyceride (TG) levels [logarithm of odds (LOD) = 3.7] on human chromosome 7q36, we examined 29 single nucleotide polymorphisms (SNPs) across INSIG1, a biological candidate gene in the region. Insulin-induced genes (INSIGs) are feedback mediators of cholesterol and fatty acid synthesis in animals, but their role in human lipid regulation is unclear. In our cohort, the INSIG1 promoter SNP rs2721 was associated with TG levels (P = 2 x 10(-3) in 1,560 individuals of the original linkage cohort, P = 8 x 10(-4) in 920 unrelated individuals of the replication cohort, combined P = 9.9 x 10(-6)). Individuals homozygous for the T allele had 9% higher TG levels and 2-fold lower expression of INSIG1 in surgical liver biopsy samples when compared with individuals homozygous for the G allele. Also, the T allele showed additional binding of nuclear proteins from HepG2 liver cells in gel shift assays. Finally, the variant rs7566605 in INSIG2, the only homolog of INSIG1, enhances the effect of rs2721 (P = 0.00117). The variant rs2721 alone explains 5.4% of the observed linkage in our cohort, suggesting that additional, yet-undiscovered genes and sequence variants in the QTL interval also contribute to alterations in TG levels in humans.

Genetic variation in cannabinoid receptor 1 (CNR1) is associated with derangements in lipid homeostasis, independent of body mass index

AIMS

In humans, genetic variation in endocannabinergic signaling has been associated with anthropometric measures of obesity. In randomized trials, pharmacological blockade at the level of the cannabinoid receptor 1 (CNR1) receptor not only facilitates weight reduction, but also improves insulin sensitivity and clinical measures of lipid homeostasis. We therefore tested the hypothesis that genetic variation in CNR1 is associated with common obesity-related metabolic disorders.

MATERIALS & METHODS

A total of six haplotype tagging SNPs were selected for CNR1, using data available within the Human HapMap (Centre d'Etude du Polymorphisme Humain population) these included: two promoter SNPs, three exonic SNPs, and a single SNP within the 3'-untranslated region. These tags were then genotyped in a rigorously phenotyped family-based collection of obese study subjects of Northern European origin.

RESULTS & CONCLUSIONS

A common CNR1 haplotype (H4; prevalence 0.132) is associated with abnormal lipid homeostasis. Additional statistical tests using single tagging SNPs revealed that these associations are partly independent of body mass index.

Mapping of quantitative trait loci for cholesterol, LDL, HDL, and triglyceride serum concentrations in pigs

The fine mapping of polymorphisms influencing cholesterol (CT), triglyceride (TG), and lipoprotein serum levels in human and mouse has provided a wealth of knowledge about the complex genetic architecture of these traits. The extension of these genetic analyses to pigs would be of utmost importance since they constitute a valuable biological and clinical model for the study of coronary artery disease and myocardial infarction. In the present work, we performed a whole genome scan for serum lipid traits in a half-sib Duroc pig population of 350 individuals. Phenotypic registers included total CT, TG, and low (LDL)- and high (HDL)-density lipoprotein serum concentrations at 45 and 190 days of age. This approach allowed us to identify two genomewide significant quantitative trait loci (QTL) for HDL-to-LDL ratio at 45 days (SSC6, 84 cM) and for TG at 190 days (SSC4, 23 cM) as well as a number of chromosomewide significant QTL. The comparison of QTL locations at 45 and 190 days revealed a notable lack of concordance at these two time points, suggesting that the effects of these QTL are age specific. Moreover, we have observed a considerable level of correspondence among the locations of the most significant porcine lipid QTL and those identified in humans. This finding might suggest that, in mammals, diverse polymorphisms located in a common set of genes are involved in the genetic variation of serum lipid levels.

A genome-wide linkage scan identifies multiple chromosomal regions influencing serum lipid levels in the population on the Samoan islands

Abnormal lipid levels are important risk factors for cardiovascular diseases. We conducted genome-wide variance component linkage analyses to search for loci influencing total cholesterol (TC), LDL, HDL and triglyceride in families residing in American Samoa and Samoa as well as in a combined sample from the two polities. We adjusted the traits for a number of environmental covariates, such as smoking, alcohol consumption, physical activity, and material lifestyle. We found suggestive univariate linkage with log of the odds (LOD) scores > 3 for LDL on 6p21-p12 (LOD 3.13) in Samoa and on 12q21-q23 (LOD 3.07) in American Samoa. Furthermore, in American Samoa on 12q21, we detected genome-wide linkage (LOD(eq) 3.38) to the bivariate trait TC-LDL. Telomeric of this region, on 12q24, we found suggestive bivariate linkage to TC-HDL (LOD(eq) 3.22) in the combined study sample. In addition, we detected suggestive univariate linkage (LOD 1.9-2.93) on chromosomes 4p-q, 6p, 7q, 9q, 11q, 12q 13q, 15q, 16p, 18q, 19p, 19q and Xq23 and suggestive bivariate linkage (LOD(eq) 2.05-2.62) on chromosomes 6p, 7q, 12p, 12q, and 19p-q. In conclusion, chromosome 6p and 12q may host promising susceptibility loci influencing lipid levels; however, the low degree of overlap between the three study samples strongly encourages further studies of the lipid-related traits.

Automated SNP genotype clustering algorithm to improve data completeness in high-throughput SNP genotyping datasets from custom arrays

High-throughput SNP genotyping platforms use automated genotype calling algorithms to assign genotypes. While these algorithms work efficiently for individual platforms, they are not compatible with other platforms, and have individual biases that result in missed genotype calls. Here we present data on the use of a second complementary SNP genotype clustering algorithm. The algorithm was originally designed for individual fluorescent SNP genotyping assays, and has been optimized to permit the clustering of large datasets generated from custom-designed Affymetrix SNP panels. In an analysis of data from a 3 K array genotyped on 1,560 samples, the additional analysis increased the overall number of genotypes by over 45,000, significantly improving the completeness of the experimental data. This analysis suggests that the use of multiple genotype calling algorithms may be advisable in high-throughput SNP genotyping experiments. The software is written in Perl and is available from the corresponding author.

Meta-analysis of genome-wide linkage studies of quantitative lipid traits in families ascertained for type 2 diabetes

Dyslipidemia is a major risk factor for coronary heart disease, which is the predominant cause of mortality in individuals with type 2 diabetes. To date, nine linkage studies for quantitative lipid traits have been performed in families ascertained for type 2 diabetes, individually yielding linkage results that were largely nonoverlapping. Discrepancies in linkage findings are not uncommon and are typically due to limited sample size and heterogeneity. To address these issues and increase the power to detect linkage, we performed a meta-analysis of all published genome scans for quantitative lipid traits conducted in families ascertained for type 2 diabetes. Statistically significant evidence (i.e., P < 0.00043) for linkage was observed for total cholesterol on 7q32.3-q36.3 (152.43-182 cM; P = 0.00004), 19p13.3-p12 (6.57-38.05 cM; P = 0.00026), 19p12-q13.13 (38.05-69.53 cM; P = 0.00001), and 19q13.13-q13.43 (69.53-101.1 cM; P = 0.00033), as well as LDL on 19p13.3-p12 (P = 0.00041). Suggestive evidence (i.e., P < 0.00860) for linkage was also observed for LDL on 19p12-q13.13, triglycerides on 7p11-q21.11 (63.72-93.29 cM), triglyceride/HDL on 7p11-q21.11 and 19p12-q13.13, and LDL/HDL on 16q11.2-q24.3 (65.2-130.4 cM) and 19p12-q13.13. Linkage for lipid traits has been previously observed on both chromosomes 7 and 19 in several unrelated studies and, together with the results of this meta-analysis, provide compelling evidence that these regions harbor important determinants of lipid levels in individuals with type 2 diabetes.

Three common intronic variants in the maternal and fetal thiamine pyrophosphokinase gene (TPK1) are associated with birth weight

Extreme variations in birth weight increase immediate postnatal mortality and morbidity, and are also associated with the predisposition to metabolic diseases in late adulthood. Birth weight in humans is influenced by yet unknown genetic factors. Since the 7q34-q35 region showed linkage with birth weight in a recent human genome scan (p = 8.10(-5)), this study investigated the TPK1 (thiamine pyrophosphokinase) gene locus, located in 7q34-36. Having found no coding variants in the TPK1 gene, we genotyped 43 non coding SNPs spanning a region of 420kb, and used the QTDT method to test their association with birth weight in 964 individuals from 220 families of European ancestry. Family-based tests detected association of 8 SNPs with birth weight (p<0.008), but after correction for multiple tests only rs228581 C/T (p = 0.03), rs228582 A/G (p = 0.04) and rs228584 C/T (p = 0.03) were still associated with birth weight, as well as their T-A-T haplotype (p = 0.03). In addition, we found an association between maternal rs228584 genotype and offspring birth weight (p = 0.027). These observations suggest that genomic variations in the fetal and maternal TPK1 gene could contribute to the variability of birth weight in normal humans.

Genome-Wide Linkage Analysis to Identify Chromosomal Regions Affecting Phenotypic Traits in the Chicken. IV. Metabolic Traits

The current study is a comprehensive genome analysis to detect QTL affecting metabolic traits in chickens. Two unique F(2) crosses generated from a commercial broiler male line and 2 genetically distinct inbred lines (Leghorn and Fayoumi) were used in the present study. The plasma glucagon, insulin, lactate, glucose, tri-iodothyronine, thyroxine, insulin-like growth factor I, and insulin-like growth factor II concentrations at 8 wk were measured in the 2 F(2) crosses. Birds were genotyped for 269 microsatellite markers across the entire genome. The program QTL Express was used for QTL detection. Significance levels were obtained using the permutation test. For the 10 traits, a total of 6 and 9 significant QTL were detected at a 1% chromosome-wise significance level, of which 1 and 6 were significant at the 5% genome-wise level for the broiler-Leghorn cross and broiler-Fayoumi cross, respectively. Most QTL for metabolic traits in the present study were detected in Gga 2, 6, 8, 9, 13, and Z for the broiler-Leghorn cross and Gga 1, 2, 4, 7, 8, 13, 17, and E47 for the broiler-Fayoumi cross. Phenotypic variation for each trait explained by all QTL across genome ranged from 2.73 to 14.08% in the broiler-Leghorn cross and from 6.93 to 21.15% in the broiler-Fayoumi cross. Several positional candidate genes within the QTL region for metabolic traits at the 1% chromosome-wise significance level are biologically associated with the regulation of metabolic pathways of insulin, triiodothyronine, and thyroxine.

Genome-wide linkage scan for loci influencing plasma triglycerides

BACKGROUND

Plasma triglyceride concentration is known to be a significant risk factor for cardiovascular disease (CVD). Previous studies have found that the level of triglycerides is strongly influenced by genetic factors.

METHODS

To identify quantitative trait loci influencing triglycerides, we conducted a genome-wide linkage scan on data from 485 Australian adult dizygotic twin pairs. Prior to linkage analysis, triglyceride values were adjusted for the effects of covariates including age, sex, time since last meal, time of blood collection (CT) and time to plasma separation.

RESULTS

The heritability estimate for ln(triglyceride) adjusted for all above fixed effects was 0.49. The highest multipoint LOD score observed was 2.94 (genome-wide p=0.049) on chromosome 7 (at 65 cM). This 7p region contains several candidate genes. Two other regions with suggestive multipoint LOD scores were also identified on chromosome 4 (LOD score=2.26 at 62 cM) and chromosome X (LOD score=2.01 at 81 cM).

CONCLUSIONS

The linkage peaks found represent newly identified regions for more detailed study, in particular the significant linkage observed on chromosome 7p13.

Comparison of linkage disequilibrium patterns between the HapMap CEPH samples and a family-based cohort of Northern European descent

The International HapMap Consortium has determined the linkage disequilibrium (LD) patterns of four major human populations. The aim of our investigation was to compare the LD patterns of the HapMap CEPH (Centre d'Etude du Polymorphisme Humain) samples with a family-based cohort of similar ancestry to determine its usefulness as a reference population for disease association studies. We examined four genomic regions on chromosomes 7q, 12p, and 14q totaling 14.3 Mb, initially identified in our linkage study of obesity and the metabolic syndrome. Near identical patterns of LD were detected in both populations. Furthermore, tagSNPs selected based on the HapMap CEPH cohort data capture over 98% of the variants at an r2 > 0.8 in the disease cohort. This confirms the usefulness of the CEPH cohort of the HapMap as a reference sample for further investigations into the genomic variation of populations of Northern European descent.

QTL mapping for genetic determinants of lipoprotein cholesterol levels in combined crosses of inbred mouse strains

To identify additional loci that influence lipoprotein cholesterol levels, we performed quantitative trait locus (QTL) mapping in offspring of PERA/EiJxI/LnJ and PERA/EiJxDBA/2J intercrosses and in a combined data set from both crosses after 8 weeks of consumption of a high fat-diet. Most QTLs identified were concordant with homologous chromosomal regions that were associated with lipoprotein levels in human studies. We detected significant new loci for HDL cholesterol levels on chromosome (Chr) 5 (Hdlq34) and for non-HDL cholesterol levels on Chrs 15 (Nhdlq9) and 16 (Nhdlq10). In addition, the analysis of combined data sets identified a QTL for HDL cholesterol on Chr 17 that was shared between both crosses; lower HDL cholesterol levels were conferred by strain PERA. This QTL colocalized with a shared QTL for cholesterol gallstone formation detected in the same crosses. Haplotype analysis narrowed this QTL, and sequencing of the candidate genes Abcg5 and Abcg8 confirmed shared alleles in strains I/LnJ and DBA/2J that differed from the alleles in strain PERA/EiJ. In conclusion, our analysis furthers the knowledge of genetic determinants of lipoprotein cholesterol levels in inbred mice and substantiates the hypothesis that polymorphisms of Abcg5/Abcg8 contribute to individual variation in both plasma HDL cholesterol levels and susceptibility to cholesterol gallstone formation.

Genome-wide linkage analysis of population variation in high-density lipoprotein cholesterol

Lower plasma levels of high-density lipoprotein cholesterol (HDL-C) are associated with the metabolic syndrome (insulin resistance, obesity, hypertension) and higher cardiovascular risk. Recent association studies have suggested rare alleles responsible for very low HDL-C levels. However, for individual cardiovascular risk factors, the majority of population-attributable deaths are associated with average rather than extreme levels. Therefore, genetic factors that determine the population variation of HDL-C are particularly relevant. We undertook genome-wide and fine mapping to identify linkage to HDL-C in healthy adult nuclear families from the Victorian Family Heart Study. In 274 adult sibling pairs (average age 24 years, average plasma HDL-C 1.4 mmol/l), genome-wide mapping revealed suggestive evidence for linkage on chromosome 4 (Z score = 3.5, 170 cM) and nominal evidence for linkage on chromosomes 1 (Z = 2.1, 176 cM) and 6 (Z = 2.6, 29 cM). Using genotypes and phenotypes from 932 subjects (233 of the sibling pairs and their parents), finer mapping of the locus on chromosome 4 strengthened our findings with a peak probability (Z score = 3.9) at 169 cM. Our linkage data suggest that chromosome 4q32.3 is linked with normal population variation in HDL-C. This region coincides with previous reports of linkage to apolipoprotein AII (a major component of HDL) and encompasses the gene encoding the carboxypeptidase E, relevant to the metabolic syndrome and HDL-C. These findings are relevant for further understanding of the genetic determinants of cardiovascular risk at a population level.

Common set of genes regulates low-density lipoprotein size and obesity-related factors in Alaskan Eskimos: Results from the GOCADAN Study

Increasing incidence of cardiovascular disease in traditionally low-risk Alaskan Eskimos is a cause for concern. The purpose of this study was to examine the genetic and environmental correlations of low-density lipoprotein (LDL) subfractions with obesity-related factors in Alaskan Eskimos, using data from the first 954 participants of the Genetics of Coronary Artery Disease in Alaska Natives Study. Estimates of genetic and environmental influence were calculated using a maximum likelihood variance component method implemented in SOLAR. Mean values of weight, body mass index (BMI), and waist were 73.4 +/- 0.5 kg, 27.6 +/- 0.2 kg/m2, and 88.0 +/- 0.4 cm, respectively. LDL, and its small (LDL1), medium (LDL2), and large (LDL3) subfractions, had mean values of 115.8 +/- 1.2 mg/dl, 8.3 +/- 0.4 mg/dl, 19.6 +/- 0.8 mg/dl, and 71.5 +/- 1.5 mg/dl, respectively. Bivariate analysis displayed significant genetic correlations between LDL subfractions and obesity-related factors: LDL1 with BMI (rhoG = 0.67, P < 0.05), waist (rhoG = 0.80, P < 0.001), and subscapular and tricep skinfolds (rhoG = 0.93, P < 0.005, and rhoG = 0.78, P < 0.05, respectively); LDL2 with BMI (rhoG = 0.52, P < 0.05), waist (rhoG = 0.46, P < 0.05), and tricep skinfold (rhoG = 0.60, P < 0.05); and mean LDL size with BMI (rhoG = -0.36), waist (rhoG = -0.42,), and subscapular and tricep skinfolds (rhoG = -0.44 and -0.43, respectively) (P < 0.005). These results show that a common set of genes is influencing LDL size and obesity-related factors in Alaskan Eskimos.

Multiple QTLs influencing triglyceride and HDL and total cholesterol levels identified in families with atherogenic dyslipidemia

We conducted a genome-wide scan using variance components linkage analysis to localize quantitative-trait loci (QTLs) influencing triglyceride (TG), high density lipoprotein-cholesterol (HDL-C), low density lipoprotein-cholesterol, and total cholesterol (TC) levels in 3,071 subjects from 459 families with atherogenic dyslipidemia. The most significant evidence for linkage to TG levels was found in a subset of Turkish families at 11q22 [logarithm of the odds ratio (LOD)=3.34] and at 17q12 (LOD=3.44). We performed sequential oligogenic linkage analysis to examine whether multiple QTLs jointly influence TG levels in the Turkish families. These analyses revealed loci at 20q13 that showed strong epistatic effects with 11q22 (conditional LOD=3.15) and at 7q36 that showed strong epistatic effects with 17q12 (conditional LOD=3.21). We also found linkage on the 8p21 region for TG in the entire group of families (LOD=3.08). For HDL-C levels, evidence of linkage was identified on chromosome 15 in the Turkish families (LOD=3.05) and on chromosome 5 in the entire group of families (LOD=2.83). Linkage to QTLs for TC was found at 8p23 in the entire group of families (LOD=4.05) and at 5q13 in a subset of Turkish and Mediterranean families (LOD=3.72). These QTLs provide important clues for the further investigation of genes responsible for these complex lipid phenotypes. These data also indicate that a large proportion of the variance of TG levels in the Turkish population is explained by the interaction of multiple genetic loci.

Genome-wide search for new genes controlling plasma lipid concentrations in mice and humans

PURPOSE OF REVIEW

Quantitative trait locus analysis has been used in both humans and mice for the purpose of finding new genes regulating plasma lipid levels. We review these methods and discuss new approaches that can help find quantitative trait locus genes.

RECENT FINDINGS

Many quantitative trait loci have been found that regulate plasma levels for HDL cholesterol (37 in mice and 30 in humans), LDL cholesterol (25 in mice and 20 in humans) and triglycerides (19 in mice and 30 in humans). Most of the human quantitative trait loci have concordant mouse quantitative trait loci mapping to homologous regions (93% for HDL cholesterol, 100% for LDL cholesterol and 80% for triglycerides), suggesting that many genes identified in mice may also regulate the same traits in humans. New approaches based on recently developed genomic and bioinformatic technologies and resources should greatly facilitate finding these genes.

SUMMARY

New genes regulating plasma lipid levels can be found in mice and then tested in humans. Some of these genes could be potential therapeutic targets for human atherosclerosis.

Genetics of Variation in HDL Cholesterol in Humans and Mice

Plasma high-density lipoprotein cholesterol (HDL-C) concentrations are genetically determined to a great extent, and quantitative trait locus (QTL) analysis has been used to identify chromosomal regions containing genes regulating HDL-C levels. We discuss new genes found to participate in HDL metabolism. We also summarize 37 mouse and 30 human QTLs for plasma HDL-C levels, finding that all but three of the mouse QTLs have been confirmed by a second cross or a homologous human QTL, that the mouse QTL map is almost saturated because 92% of recently reported QTLs are repeats of those already found, and that 28 of the 30 human QTLs are located in regions homologous to mouse QTLs. This high degree of concordance between mouse and human QTLs suggests that the underlying genes may be the same. Strategies to more rapidly identify genes underlying mouse and human QTLs for HDL-C include focusing on the mouse and using mouse–human homologies, combining crosses, and haplotyping to narrow the region. Sequence analysis and expression studies can distinguish candidate genes consistent across multiple mouse crosses, and testing the candidate genes in human association studies can provide additional evidence for the candidacy of a gene. Together these strategies can accelerate the pace of finding genes that regulate HDL.

A genome scan for serum triglyceride in obese nuclear families

Serum triglyceride (TG) levels are increased in extremely obese individuals, indicating abnormalities in lipid metabolism and insulin resistance. We carried out a genome scan for serum TG in 320 nuclear families segregating extreme obesity and normal weight. Three hundred eighty-two Marshfield microsatellite markers (Screening Set 11) were genotyped. Quantitative linkage analyses were performed using family regression and variance components methods. We found linkage on the 7q36 region [D7S3058, 174 centimorgan (cM), Logarithm of Odds (LOD) = 2.98] for log-transformed TG. We also found suggestive linkages on chromosomes 20 (D20S164, 101 cM, LOD = 2.34), 13 (111 cM, LOD = 2.00), and 9 (104 cM, LOD = 1.90) as well as some weaker trends for chromosomes 1, 3, 5, 10, 12, and 22. In 58 African American families, LOD scores of 3.66 and 2.62 were observed on two loci on chromosome 16: D16S3369 (64 cM) and MFD466 (100 cM). To verify the 7q36 linkage, we added 60 nuclear families, and the LOD score increased to 3.52 (empirical P < 0.002) on marker D7S3058.