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

Genome-wide association (GWA) studies represent a powerful strategy for identifying susceptibility genes for complex diseases in human populations but results must be confirmed and replicated. Because of the close homology between mouse and human genomes, the mouse can be used to add evidence to genes suggested by human studies. We used the mouse quantitative trait loci (QTL) map to interpret results from a GWA study for genes associated with plasma HDL cholesterol levels. We first positioned single nucleotide polymorphisms (SNPs) from a human GWA study on the genomic map for mouse HDL QTL. We then used mouse bioinformatics, sequencing, and expression studies to add evidence for one well-known HDL gene (Abca1) and three newly identified genes (Galnt2, Wwox, and Cdh13), thus supporting the results of the human study. For GWA peaks that occur in human haplotype blocks with multiple genes, we examined the homologous regions in the mouse to prioritize the genes using expression, sequencing, and bioinformatics from the mouse model, showing that some genes were unlikely candidates and adding evidence for candidate genes Mvk and Mmab in one haplotype block and Fads1 and Fads2 in the second haplotype block. Our study highlights the value of mouse genetics for evaluating genes found in human GWA studies.     

Anti-inflammatory and cholesterol-reducing properties of apolipoprotein mimetics: a review

Reduced levels of HDL cholesterol (HDL-C) are a strong independent predictor of coronary artery disease (CAD) risk. The major anti-atherogenic function of HDL is to mediate reverse cholesterol transport. This response is highly dependent on apoA-I and apoE, protein components of HDL. Randomized clinical trials have assessed effects of several classes of drugs on plasma cholesterol levels in CAD patients. Agents including cholestyramine, fibrates, niacin, and statins significantly lower LDL cholesterol (LDL-C) and induce modest increases in HDL-C, but tolerance issues and undesirable side effects are common. Additionally, residual risk may be present in patients with persistently low HDL-C and other complications despite a reduction in LDL-C. These observations have fueled interest in the development of new pharmacotherapies that positively impact circulating lipoproteins. The goal of this review is to discuss the therapeutic potential of synthetic apolipoprotein mimetic peptides. These include apoA-I mimetic peptides that have undergone initial clinical assessment. We also discuss newer apoE mimetics that mediate the clearance of atherogenic lipids from the circulation and possess anti-inflammatory properties. One of these (AEM-28) has recently been given orphan drug status and is undergoing clinical trials.     

Genome-wide linkage analyses and candidate gene fine mapping for HDL3 cholesterol: the Framingham Study

High density lipoprotein cholesterol (HDL-C) is inversely associated with coronary heart disease and has a genetic component; however, linkage to HDL-C is not conclusive. Subfractions of HDL, such as HDL(3)-C, may be better phenotypes for linkage studies. Using HDL(3)-C levels measured on 907 Framingham Heart Study subjects from 330 families around 1987, we conducted a genome-wide variance components linkage analysis with 401 microsatellite markers spaced approximately 10 centimorgan (cM) apart. Nine candidate genes were identified and annotated using a bioinformatics approach in the region of the highest linkage peak. Twenty-eight single nucleotide polymorphisms (SNPs) were selected from these candidate genes, and linkage and family-based association fine mapping were conducted using these SNPs. The highest multipoint log-of-the-odds (LOD) score from the initial linkage analysis was 3.7 at 133 cM on chromosome 6. Linkage analyses with additional SNPs yielded the highest LOD score of 4.0 at 129 cM on chromosome 6. Family-based association analysis revealed that SNP rs2257104 in PLAGL1 at approximately 143 cM was associated with multivariable adjusted HDL(3) (P = 0.03). Further study of the linkage region and exploration of other variants in PLAGL1 are warranted to define the potential functional variants of HDL-C metabolism.     

综述: HDL蛋白质组分临床研究新进展

高密度脂蛋白胆固醇(HDL-C)水平与冠心病风险呈负相关,低HDL-C水平增加心血管疾病风险,是心血管疾病的独立危险因素．然而升高HDL-C水平的药物治疗并没有明显的临床获益,没有起到降低心血管疾病风险的预期效果,因此高密度脂蛋白(HDL)功能比HDL-C水平更好地预测心血管事件的发生．HDL是蛋白质含量最高的脂蛋白,由于蛋白质组学技术的进步,越来越多的HDL蛋白质成分被发现,除了传统的载脂蛋白、酶类,还包括脂质转移蛋白、急性期反应蛋白、补体成分、蛋白酶抑制剂,HDL的功能也从脂质转运扩展到感染免疫、急性期反应、补体激活、离子结合等,不仅参与动脉粥样硬化的发生发展,在终末期肾病、糖尿病等高心血管风险疾病中也发挥重要作用．本文就HDL蛋白质成分、功能及在冠心病和高心血管风险疾病中的作用做一综述．     

Genetics of Callous-Unemotional Behavior in Children

Callous-unemotional behavior (CU) is currently under consideration as a subtyping index for conduct disorder diagnosis. Twin studies routinely estimate the heritability of CU as greater than 50%. It is now possible to estimate genetic influence using DNA alone from samples of unrelated individuals, not relying on the assumptions of the twin method. Here we use this new DNA method (implemented in a software package called Genome-wide Complex Trait Analysis, GCTA) for the first time to estimate genetic influence on CU. We also report the first genome-wide association (GWA) study of CU as a quantitative trait. We compare these DNA results to those from twin analyses using the same measure and the same community sample of 2,930 children rated by their teachers at ages 7, 9 and 12. GCTA estimates of heritability were near zero, even though twin analysis of CU in this sample confirmed the high heritability of CU reported in the literature, and even though GCTA estimates of heritability were substantial for cognitive and anthropological traits in this sample. No significant associations were found in GWA analysis, which, like GCTA, only detects additive effects of common DNA variants. The phrase ‘missing heritability’ was coined to refer to the gap between variance associated with DNA variants identified in GWA studies versus twin study heritability. However, GCTA heritability, not twin study heritability, is the ceiling for GWA studies because both GCTA and GWA are limited to the overall additive effects of common DNA variants, whereas twin studies are not. This GCTA ceiling is very low for CU in our study, despite its high twin study heritability estimate. The gap between GCTA and twin study heritabilities will make it challenging to identify genes responsible for the heritability of CU.     

Genome-Wide Association Analysis of Tolerance to Methylmercury Toxicity in Drosophila Implicates Myogenic and Neuromuscular Developmental Pathways

Methylmercury (MeHg) is a persistent environmental toxin present in seafood that can compromise the developing nervous system in humans. The effects of MeHg toxicity varies among individuals, despite similar levels of exposure, indicating that genetic differences contribute to MeHg susceptibility. To examine how genetic variation impacts MeHg tolerance, we assessed developmental tolerance to MeHg using the sequenced, inbred lines of the Drosophila melanogaster Genetic Reference Panel (DGRP). We found significant genetic variation in the effects of MeHg on development, measured by eclosion rate, giving a broad sense heritability of 0.86. To investigate the influence of dietary factors, we measured MeHg toxicity with caffeine supplementation in the DGRP lines. We found that caffeine counteracts the deleterious effects of MeHg in the majority of lines, and there is significant genetic variance in the magnitude of this effect, with a broad sense heritability of 0.80. We performed genome-wide association (GWA) analysis for both traits, and identified candidate genes that fall into several gene ontology categories, with enrichment for genes involved in muscle and neuromuscular development. Overexpression of glutamate-cysteine ligase, a MeHg protective enzyme, in a muscle-specific manner leads to a robust rescue of eclosion of flies reared on MeHg food. Conversely, mutations in kirre, a pivotal myogenic gene identified in our GWA analyses, modulate tolerance to MeHg during development in accordance with kirre expression levels. Finally, we observe disruptions of indirect flight muscle morphogenesis in MeHg-exposed pupae. Since the pathways for muscle development are evolutionarily conserved, it is likely that the effects of MeHg observed in Drosophila can be generalized across phyla, implicating muscle as an additional hitherto unrecognized target for MeHg toxicity. Furthermore, our observations that caffeine can ameliorate the toxic effects of MeHg show that nutritional factors and dietary manipulations may offer protection against the deleterious effects of MeHg exposure.     

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.     

A Genome-Wide Association Analysis Reveals Epistatic Cancellation of Additive Genetic Variance for Root Length in Arabidopsis thaliana

Efforts to identify loci underlying complex traits generally assume that most genetic variance is additive. Here, we examined the genetics of Arabidopsis thaliana root length and found that the genomic narrow-sense heritability for this trait in the examined population was statistically zero. The low amount of additive genetic variance that could be captured by the genome-wide genotypes likely explains why no associations to root length could be found using standard additive-model-based genome-wide association (GWA) approaches. However, as the broad-sense heritability for root length was significantly larger, and primarily due to epistasis, we also performed an epistatic GWA analysis to map loci contributing to the epistatic genetic variance. Four interacting pairs of loci were revealed, involving seven chromosomal loci that passed a standard multiple-testing corrected significance threshold. The genotype-phenotype maps for these pairs revealed epistasis that cancelled out the additive genetic variance, explaining why these loci were not detected in the additive GWA analysis. Small population sizes, such as in our experiment, increase the risk of identifying false epistatic interactions due to testing for associations with very large numbers of multi-marker genotypes in few phenotyped individuals. Therefore, we estimated the false-positive risk using a new statistical approach that suggested half of the associated pairs to be true positive associations. Our experimental evaluation of candidate genes within the seven associated loci suggests that this estimate is conservative; we identified functional candidate genes that affected root development in four loci that were part of three of the pairs. The statistical epistatic analyses were thus indispensable for confirming known, and identifying new, candidate genes for root length in this population of wild-collected A. thaliana accessions. We also illustrate how epistatic cancellation of the additive genetic variance explains the insignificant narrow-sense and significant broad-sense heritability by using a combination of careful statistical epistatic analyses and functional genetic experiments.     

Recalculation of 23 mouse HDL QTL datasets improves accuracy and allows for better candidate gene analysis

In the past 15 years, the quantitative trait locus (QTL) mapping approach has been applied to crosses between different inbred mouse strains to identify genetic loci associated with plasma HDL cholesterol levels. Although successful, a disadvantage of this method is low mapping resolution, as often several hundred candidate genes fall within the confidence interval for each locus. Methods have been developed to narrow these loci by combining the data from the different crosses, but they rely on the accurate mapping of the QTL and the treatment of the data in a consistent manner. We collected 23 raw datasets used for the mapping of previously published HDL QTL and reanalyzed the data from each cross using a consistent method and the latest mouse genetic map. By utilizing this approach, we identified novel QTL and QTL that were mapped to the wrong part of chromosomes. Our new HDL QTL map allows for reliable combining of QTL data and candidate gene analysis, which we demonstrate by identifying Grin3a and Etv6, as candidate genes for QTL on chromosomes 4 and 6, respectively. In addition, we were able to narrow a QTL on Chr 19 to five candidates.     

Introduction to Deep Sequencing and Its Application to Drug Addiction Research with a Focus on Rare Variants

Through linkage analysis, candidate gene approach, and genome-wide association studies (GWAS), many genetic susceptibility factors for substance dependence have been discovered such as the alcohol dehydrogenase gene (ALDH2) for alcohol dependence (AD) and nicotinic acetylcholine receptor (nAChR) subunit variants on chromosomes 8 and 15 for nicotine dependence (ND). However, these confirmed genetic factors contribute only a small portion of the heritability responsible for each addiction. Among many potential factors, rare variants in those identified and unidentified susceptibility genes are supposed to contribute greatly to the missing heritability. Several studies focusing on rare variants have been conducted by taking advantage of next-generation sequencing technologies, which revealed that some rare variants of nAChR subunits are associated with ND in both genetic and functional studies. However, these studies investigated variants for only a small number of genes and need to be expanded to broad regions/genes in a larger population. This review presents an update on recently developed methods for rare-variant identification and association analysis and on studies focused on rare-variant discovery and function related to addictions.     

The molecular genetics of type 1 diabetes: new genes and emerging mechanisms

Susceptibility to type 1 diabetes (T1D) is determined by complex interactions between several genetic loci and environmental factors. Alleles at the human leukocyte antigen (HLA) locus explain up to 50% of the familial clustering of T1D, and the remainder is contributed to by multiple loci, of which only four were known until recently. First-stage results of genome-wide association (GWA) studies performed with high-density genotyping arrays have already produced four novel loci and the promise that, with the completion of the second stage of the GWA studies, most of the genetic basis of T1D will be known. We will review what is known to date about the mechanisms of genetic susceptibility to T1D, with special emphasis on possible diagnostic and therapeutic applications of these recent genetic findings.     

A variational Bayes algorithm for fast and accurate multiple locus genome-wide association analysis

Background  

The success achieved by genome-wide association (GWA) studies in the identification of candidate loci for complex diseases has been accompanied by an inability to explain the bulk of heritability. Here, we describe the algorithm V-Bay, a variational Bayes algorithm for multiple locus GWA analysis, which is designed to identify weaker associations that may contribute to this missing heritability.     

Mining the LIPG allelic spectrum reveals the contribution of rare and common regulatory variants to HDL cholesterol

Genome-wide association studies (GWAS) have successfully identified loci associated with quantitative traits, such as blood lipids. Deep resequencing studies are being utilized to catalogue the allelic spectrum at GWAS loci. The goal of these studies is to identify causative variants and missing heritability, including heritability due to low frequency and rare alleles with large phenotypic impact. Whereas rare variant efforts have primarily focused on nonsynonymous coding variants, we hypothesized that noncoding variants in these loci are also functionally important. Using the HDL-C gene LIPG as an example, we explored the effect of regulatory variants identified through resequencing of subjects at HDL-C extremes on gene expression, protein levels, and phenotype. Resequencing a portion of the LIPG promoter and 5' UTR in human subjects with extreme HDL-C, we identified several rare variants in individuals from both extremes. Luciferase reporter assays were used to measure the effect of these rare variants on LIPG expression. Variants conferring opposing effects on gene expression were enriched in opposite extremes of the phenotypic distribution. Minor alleles of a common regulatory haplotype and noncoding GWAS SNPs were associated with reduced plasma levels of the LIPG gene product endothelial lipase (EL), consistent with its role in HDL-C catabolism. Additionally, we found that a common nonfunctional coding variant associated with HDL-C (rs2000813) is in linkage disequilibrium with a 5' UTR variant (rs34474737) that decreases LIPG promoter activity. We attribute the gene regulatory role of rs34474737 to the observed association of the coding variant with plasma EL levels and HDL-C. Taken together, the findings show that both rare and common noncoding regulatory variants are important contributors to the allelic spectrum in complex trait loci.     

Targeted next-generation sequencing to diagnose disorders of HDL cholesterol

A low level of HDL cholesterol (HDL-C) is a common clinical scenario and an important marker for increased cardiovascular risk. Many patients with very low or very high HDL-C have a rare mutation in one of several genes, but identification of the molecular abnormality in patients with extreme HDL-C is rarely performed in clinical practice. We investigated the accuracy and diagnostic yield of a targeted next-generation sequencing (NGS) assay for extreme levels of HDL-C. We developed a targeted NGS panel to capture the exons, intron/exon boundaries, and untranslated regions of 26 genes with highly penetrant effects on plasma lipid levels. We sequenced 141 patients with extreme HDL-C levels and prioritized variants in accordance with medical genetics guidelines. We identified 35 pathogenic and probably pathogenic variants in HDL genes, including 21 novel variants, and performed functional validation on a subset of these. Overall, a molecular diagnosis was established in 35.9% of patients with low HDL-C and 5.2% with high HDL-C, and all prioritized variants identified by NGS were confirmed by Sanger sequencing. Our results suggest that a molecular diagnosis can be identified in a substantial proportion of patients with low HDL-C using targeted NGS.     

Molecular genetics of myocardial infarction

Myocardial infarction (MI) is an important clinical problem because of its large contribution to mortality. The main causal and treatable risk factors for MI include hypertension, hypercholesterolemia or dyslipidemia, diabetes mellitus, and smoking. In addition to these risk factors, recent studies have shown the importance of genetic factors and interactions between multiple genes and environmental factors. Disease prevention is an important strategy for reducing the overall burden of MI, with the identification of markers for disease risk being key both for risk prediction and for potential intervention to lower the chance of future events. Although genetic linkage analyses of families and sib-pairs as well as candidate gene and genome-wide association studies have implicated several loci and candidate genes in predisposition to coronary heart disease (CHD) or MI, the genes that contribute to genetic susceptibility to these conditions remain to be identified definitively. In this review, we summarize both candidate loci for CHD or MI identified by linkage analyses and candidate genes examined by association studies. We also review in more detail studies that have revealed the association with MI or CHD of polymorphisms in MTHFR, LPL, and APOE by the candidate gene approach and those in LTA and at chromosomal region 9p21.3 by genome-wide scans. Such studies may provide insight into the function of implicated genes as well as into the role of genetic factors in the development of CHD and MI.     

Gene-set based genome-wide association analysis for the speed of sound in two skeletal sites of Korean women

The speed of sound (SOS) value is an indicator of bone mineral density (BMD). Previous genome-wide association (GWA) studies have identified a number of genes, whose variations may affect BMD levels. However, their biological implications have been elusive. We re-analyzed the GWA study dataset for the SOS values in skeletal sites of 4,659 Korean women, using a gene-set analysis software, GSA-SNP. We identified 10 common representative GO terms, and 17 candidate genes between these two traits (P_GS ＜ 0.05). Implication of these GO terms and genes in the bone mechanism is well supported by the literature survey. Interestingly, the significance levels of some member genes were inversely related, in several gene-sets that were shared between two skeletal sites. This implies that biological process, rather than SNP or gene, is the substantial unit of genetic association for SOS in bone. In conclusion, our findings may provide new insights into the biological mechanisms for BMD. [BMB Reports 2014; 47(6): 348-353]     

Whole-exome sequencing reveals damaging gene variants associated with hypoalphalipoproteinemia

Low levels of high density lipoprotein-cholesterol (HDL-C) are associated with an elevated risk of arteriosclerotic coronary heart disease. Heritability of HDL-C levels is high. In this research discovery study, we used whole-exome sequencing to identify damaging gene variants that may play significant roles in determining HDL-C levels. We studied 204 individuals with a mean HDL-C level of 27.8 ± 6.4 mg/dl (range: 4–36 mg/dl). Data were analyzed by statistical gene burden testing and by filtering against candidate gene lists. We found 120 occurrences of probably damaging variants (116 heterozygous; four homozygous) among 45 of 104 recognized HDL candidate genes. Those with the highest prevalence of damaging variants were ABCA1 (n = 20), STAB1 (n = 9), OSBPL1A (n = 8), CPS1 (n = 8), CD36 (n = 7), LRP1 (n = 6), ABCA8 (n = 6), GOT2 (n = 5), AMPD3 (n = 5), WWOX (n = 4), and IRS1 (n = 4). Binomial analysis for damaging missense or loss-of-function variants identified the ABCA1 and LDLR genes at genome-wide significance. In conclusion, whole-exome sequencing of individuals with low HDL-C showed the burden of damaging rare variants in the ABCA1 and LDLR genes is particularly high and revealed numerous occurrences in HDL candidate genes, including many genes identified in genome-wide association study reports. Many of these genes are involved in cancer biology, which accords with epidemiologic findings of the association of HDL deficiency with increased risk of cancer, thus presenting a new area of interest in HDL genomics.     

GWAPower: a statistical power calculation software for genome-wide association studies with quantitative traits

Background

In designing genome-wide association (GWA) studies it is important to calculate statistical power. General statistical power calculation procedures for quantitative measures often require information concerning summary statistics of distributions such as mean and variance. However, with genetic studies, the effect size of quantitative traits is traditionally expressed as heritability, a quantity defined as the amount of phenotypic variation in the population that can be ascribed to the genetic variants among individuals. Heritability is hard to transform into summary statistics. Therefore, general power calculation procedures cannot be used directly in GWA studies. The development of appropriate statistical methods and a user-friendly software package to address this problem would be welcomed.

Results

This paper presents GWAPower, a statistical software package of power calculation designed for GWA studies with quantitative traits, where genetic effect is defined as heritability. Based on several popular one-degree-of-freedom genetic models, this method avoids the need to specify the non-centrality parameter of the F-distribution under the alternative hypothesis. Therefore, it can use heritability information directly without approximation. In GWAPower, the power calculation can be easily adjusted for adding covariates and linkage disequilibrium information. An example is provided to illustrate GWAPower, followed by discussions.

Conclusions

GWAPower is a user-friendly free software package for calculating statistical power based on heritability in GWA studies with quantitative traits. The software is freely available at: http://dl.dropbox.com/u/10502931/GWAPower.zip     

Where are the missing pieces of the schizophrenia genetics puzzle?

On the basis of recent data from candidate region/gene and genome-wide association studies (GWAS) and their follow-up investigations, the number of genes potentially implicated in schizophrenia has been estimated to be over 1000. However, with regard to the identified odds ratio, it is likely that genetic variants with more definitive effect on schizophrenia phenotype are still missing. The hunt therefore remains open for the genetic variants that would explain the majority of the missing heritability of schizophrenia. This review aims at summarizing data from recent DNA microarray and target gene/region resequencing in order to propose new insights of where to look next. The review is divided into three sections: GWAS, copy-number variations and rare variant--candidate gene resequencing.