Lipoprotein candidate genes for multivariate factors of the insulin resistance syndrome: a sib-pair linkage analysis in women twins.

The insulin resistance syndrome (IRS) is characterized by a combination of interrelated coronary heart disease risk factors, including low high-density lipoprotein cholesterol (HDLC) levels, obesity and increases in triglyceride (TG), systolic and diastolic blood pressure (BP), small low-density lipoprotein particles (LDL-size), and fasting and postload plasma insulin and glucose. Using factor analysis, we previously identified multivariate factors based on data from women participating in the Kaiser Permanente Women Twins Study: 1) Weight/Fat, 2) Insulin/Glucose, 3) Lipids, and 4) BP. The purpose of this study is to evaluate evidence for genetic linkage between the multivariate factors and candidate genes. Quantitative sib-pair analysis based on the factor scores with markers for 9 candidate genes was carried out based on data from 126 pairs of dizygotic (DZ) women twins from the second exam of the Kaiser Permanente Women Twins study. Suggestive evidence for linkage was found for the Weight/fat factor and the Apo E gene (p = 0.01), and stronger evidence for linkage with the Lipid factor and the cholesterol ester transfer protein (p = 0.002) gene. Therefore, the CETP gene appears to influence covariation in LDL size, TG, and HDL, and may account for a portion of the well-established statistical and metabolic associations observed between these risk factors.     

Accurate inference of relationships in sib-pair linkage studies.

Relative-pair designs are routinely employed in linkage studies of complex genetic diseases and quantitative traits. Valid application of these methods requires correct specification of the relationships of the pairs. For example, within a sibship, presumed full sibs actually might be MZ twins, half sibs, or unrelated. Misclassification of half-sib pairs or unrelated individuals as full sibs can result in reduced power to detect linkage. When other family members, such as parents or additional siblings, are available, incorrectly specified relationships usually will be detected through apparent incompatibilities with Mendelian inheritance. Without other family members, sibling relationships cannot be determined absolutely, but they still can be inferred probabilistically if sufficient genetic marker data are available. In this paper, we describe a simple likelihood ratio method to infer the true relationship of a putative sibling pair. We explore the number of markers required to accurately infer relationships typically encountered in a sib-pair study, as a function of marker allele frequencies, marker spacing, and genotyping error rate, and we conclude that very accurate inference of relationships can be achieved, given the marker data from even part of a genome scan. We compare our method to related methods of relationship inference that have been suggested. Finally, we demonstrate the value of excluding non-full sibs in a genetic linkage study of non-insulin-dependent diabetes mellitus.     

Sib-pair linkage analysis of longitudinal changes in lipoprotein risk factors and lipase genes in women twins

Based on longitudinal twin data in women, we have previously demonstrated a genetic influence on changes in lipoprotein risk factors, blood pressure measurements, and body mass index over a decade. The present study examined the linkage between changes in lipoprotein variables and candidate genes encoding the hormone-sensitive lipase (HSL), hepatic lipase (HL), and lipoprotein lipase (LPL). The sample consisted of 126 dizygotic (DZ) pairs of women twins who participated in the two examinations of the Kaiser Permanente Women Twins Study, performed a decade apart. Using quantitative sib-pair linkage analysis, a linkage was demonstrated between the locus for hormone-sensitive lipase and age-adjusted changes in plasma triglyceride (P = 0.015), which became more significant after adjustment for environmental factors and the exam-1 level (P = 0.005). There was also evidence suggesting linkage between the locus for hepatic lipase and changes in triglyceride (P = 0.023), but no linkage was detected for lipoprotein lipase and changes of lipid levels with time. These findings suggest that variation at these candidate gene loci may underlie a portion of the intraindividual variations in these coronary heart disease (CHD) risk factors, and that studies to identify the functional variants could provide new insights into genetic susceptibility to cardiovascular disease.     

Combined linkage and association sib-pair analysis for quantitative traits.

An extension to current maximum-likelihood variance-components procedures for mapping quantitative-trait loci in sib pairs that allows a simultaneous test of allelic association is proposed. The method involves modeling of the allelic means for a test of association, with simultaneous modeling of the sib-pair covariance structure for a test of linkage. By partitioning of the mean effect of a locus into between- and within-sibship components, the method controls for spurious associations due to population stratification and admixture. The power and efficacy of the method are illustrated through simulation of various models of both real and spurious association.     

Selection strategies for linkage studies using twins.

Genetic linkage analysis for complex diseases offers a major challenge to geneticists. In these complex diseases multiple genetic loci are responsible for the disease and they may vary in the size of their contribution; the effect of any single one of them is likely to be small. In many situations, like in extensive twin registries, trait values have been recorded for a large number of individuals, and preliminary studies have revealed summary measures for those traits, like mean, variance and components of variance, including heritability. Given the small effect size, a random sample of twins will require a prohibitively large sample size. It is well known that selective sampling is far more efficient in terms of genotyping effort. In this paper we derive easy expressions for the information contributed by sib pairs for the detection of linkage to a quantitative trait locus (QTL). We consider random samples as well as samples of sib pairs selected on the basis of their trait values. These expressions can be rapidly computed and do not involve simulation. We extend our results for quantitative traits to dichotomous traits using the concept of a liability threshold model. We present tables with required sample sizes for height, insulin levels and migraine, three of the traits studied in the GenomEUtwin project.     

Refining phenotype characterization in genetic linkage studies of schizophrenia.

A definitive replicable genetic linkage for a major locus underlying the susceptibility to schizophrenia has not been identified to date. Although there are several possible explanations for the failure to find linkage in schizophrenia, one major problem is that the range of phenotypic expressions of the genes for schizophrenia has not been clarified. A more refined understanding of the various phenotypic expressions of a gene related to schizophrenia would enhance the power of studies designed to detect a genetic linkage with a major chromosomal locus and would benefit other strategies for understanding the etiology of schizophrenia. The genes for schizophrenia may be frequently expressed in relatives of schizophrenic patients, although with less severe symptoms than those of chronic schizophrenia. Two series of findings support this notion. Nonschizophrenic relatives of schizophrenic patients demonstrate an increased incidence of nonpsychotic schizophrenia-like symptoms and traits, and they manifest deficit performances on several different laboratory tests of neurocognitive functioning. A more refined phenotypic expression of a schizophrenia-related gene may thus be indicated by personality traits and subclinical neurocognitive deficits. These personality traits and neurocognitive deficits are considered here as possible aids in the identification of affected cases in genetic linkage studies of schizophrenia. Terminology for different indicators of neurocognitive deficits is introduced, and the relative utility of personality traits and indicators of neurocognitive deficit for genetic linkage studies is discussed. As specific examples, schizophrenia-related personality traits that are unrelated to affective symptoms and performance deficits on tasks of eye tracking and continuous attention are considered for strategies for broadening phenotype characterization without reducing the specificity of affected case identification.     

Contribution of the hepatic lipase gene to the atherogenic lipoprotein phenotype in familial combined hyperlipidemia

Familial combined hyperlipidemia (FCH) is a common genetic lipid disorder with a frequency of 1-2% in the population. In addition to the hypercholesterolemia and/or hypertriglyceridemia that affected individuals exhibit, small, dense LDL particles and decreased HDL-cholesterol levels are traits frequently associated with FCH. Recently, we reported that families with FCH and families enriched for coronary artery disease (CAD) share genetic determinants for the atherogenic lipoprotein phenotype (ALP), a profile presenting with small, dense LDL particles, decreased HDL-cholesterol levels, and increased triglyceride levels. Other studies in normolipidemic populations have shown that the hepatic lipase (HL) gene is linked to HDL-cholesterol levels and that a polymorphism within the HL promoter (-514C-->T) is associated with increased HDL-cholesterol levels as well as larger, more buoyant LDL particles. In the present study, we tested whether the HL gene locus also contributes to ALP in a series of Dutch FCH families using nonparametric sibpair linkage analysis and association analysis. Evidence for linkage of LDL particle size (P < 0.019), HDL-cholesterol (P < 0.003), and triglyceride levels (P < 0.026) to the HL gene locus was observed. A genome scan in a subset of these families exhibited evidence for linkage of PPD (LOD = 2.2) and HDL-cholesterol levels (LOD = 1.2) to the HL gene locus as well. The -514C-->T promoter polymorphism was significantly associated (P < 0.0001) with higher HDL-cholesterol levels in the unrelated males of this population, but not in unrelated females. No association was observed between the polymorphism and LDL particle size or triglyceride levels. Our results provide support that ALP is a multigenic trait and suggest that the relationship between small, dense LDL particles, HDL-cholesterol, and triglyceride levels in FCH families is due, in part, to common genetic factors.     

Power of sib-pair and sib-trio linkage analysis with assortative mating and multiple disease loci.

Sib-pair linkage analysis has been proposed for identifying genes that predispose to common diseases. We have shown that the presence of assortative mating and multiple disease-susceptibility loci (genetic heterogeneity) can increase the required sample size for affected-affected sib pairs several fold over the sample size required under random mating. We propose a new test statistic based on sib trios composed of either one unaffected and two affected siblings or one affected and two unaffected siblings. The sample-size requirements under assortative mating and multiple disease loci for these sib-trio statistics are much smaller, under most conditions, than the corresponding sample sizes for sib pairs. Study designs based on data from sib trios with one or two affected members are recommended whenever assortative mating and genetic heterogeneity are suspected.     

Improved power of sib-pair linkage analysis using measures of complex trait dynamics

The influence of epistasis on a quantitative trait can reduce the power of linkage analysis to identify the underlying loci. In the present study, we simulated a complex trait derived from a dynamic one-locus gene expression system with epistasis arising from feedback regulation and tested the power of sib-pair linkage analysis methods for detecting the underlying quantitative trait locus (QTL). Using this simple genetic architecture, we demonstrate that the power of sib-pair linkage analysis can be greatly improved if measures of complex trait dynamics are considered.     

Parent ratings of temperament in twins: explaining the 'too low' DZ correlations.

Twin studies of child temperament using objective measures consistently suggest moderate heritability for most dimensions. However, parent rating measures produce unusual patterns of results. Intraclass correlations for identical (MZ) twins are typically high, whereas fraternal (DZ) twin intraclass correlations are much lower than would be predicted from an additive genetic model. The 'too low' DZ correlations can be explained by parent-rating biases that either exaggerate the differences between DZ twins (contrast effects) or that inflate the similarity of MZ twins (assimilation effects), or by the presence of non-additive genetic variance. To evaluate the three possible explanations, we used model-fitting procedures applied to parent-rating data averaged across 14, 20, 24, and 36 months of age in a sample of 196 twin pairs participating in the MacArthur Longitudinal Twin Study. The data were best described by a model that included contrast effects. Implications for non-twin research are discussed.     

Genetic linkage between lipoprotein(a) phenotype and a DNA polymorphism in the plasminogen gene

Coronary heart disease risk correlates directly with plasma concentrations of lipoprotein(a) (Lp(a)), a low-density lipoprotein-like particle distinguished by the presence of the glycoprotein apolipoprotein(a) (apo(a)), which is bound to apolipoprotein B-100 (apoB-100) by disulfide bridges. Size isoforms of apo(a) are inherited as Mendelian codominant traits and are associated with variations in the plasma concentration of lipoprotein(a). Plasminogen and apo(a) show striking protein sequence homology, and their genes both map to chromosome 6q26-27. In a large family with early coronary heart disease and high plasma concentrations of Lp(a), we found tight linkage between apo(a) size isoforms and a DNA polymorphism in the plasminogen gene; plasma concentrations of Lp(a) also appeared to be related to genetic variation at the apo(a) locus. We found free recombination between the same phenotype and alleles of the apoB DNA polymorphism. This suggests that apo(a) size isoforms and plasma lipoprotein(a) concentrations are each determined by genetic variation at the apo(a) locus.     

Importance sampling method of correction for multiple testing in affected sib-pair linkage analysis

Using the Genetic Analysis Workshop 13 simulated data set, we compared the technique of importance sampling to several other methods designed to adjust p-values for multiple testing: the Bonferroni correction, the method proposed by Feingold et al., and na?ve Monte Carlo simulation. We performed affected sib-pair linkage analysis for each of the 100 replicates for each of five binary traits and adjusted the derived p-values using each of the correction methods. The type I error rates for each correction method and the ability of each of the methods to detect loci known to influence trait values were compared. All of the methods considered were conservative with respect to type I error, especially the Bonferroni method. The ability of these methods to detect trait loci was also low. However, this may be partially due to a limitation inherent in our binary trait definitions.     

Refining phenotype characterization in genetic linkage studies of schizophrenia

Abstract

A definitive replicable genetic linkage for a major locus underlying the susceptibility to schizophrenia has not been identified to date. Although there are several possible explanations for the failure to find linkage in schizophrenia, one major problem is that the range of phenotypic expressions of the genes for schizophrenia has not been clarified. A more refined understanding of the various phenotypic expressions of a gene related to schizophrenia would enhance the power of studies designed to detect a genetic linkage with a major chromosomal locus and would benefit other strategies for understanding the etiology of schizophrenia.

The genes for schizophrenia may be frequently expressed in relatives of schizophrenic patients, although with less severe symptoms than those of chronic schizophrenia. Two series of findings support this notion. Nonschizophrenic relatives of schizophrenic patients demonstrate an increased incidence of nonpsychotic schizophrenia‐like symptoms and traits, and they manifest deficit performances on several different laboratory tests of neurocognitive functioning. A more refined phenotypic expression of a schizophrenia‐related gene may thus be indicated by personality traits and subclinical neurocognitive deficits.

These personality traits and neurocognitive deficits are considered here as possible aids in the identification of affected cases in genetic linkage studies of schizophrenia. Terminology for different indicators of neurocognitive deficits is introduced, and the relative utility of personality traits and indicators of neurocognitive deficit for genetic linkage studies is discussed. As specific examples, schizophrenia‐related personality traits that are unrelated to affective symptoms and performance deficits on tasks of eye tracking and continuous attention are considered for strategies for broadening phenotype characterization without reducing the specificity of affected case identification.     

Characterizing the metabolic phenotype: a phenotype phase plane analysis.

Genome-scale metabolic maps can be reconstructed from annotated genome sequence data, biochemical literature, bioinformatic analysis, and strain-specific information. Flux-balance analysis has been useful for qualitative and quantitative analysis of metabolic reconstructions. In the past, FBA has typically been performed in one growth condition at a time, thus giving a limited view of the metabolic capabilities of a metabolic network. We have broadened the use of FBA to map the optimal metabolic flux distribution onto a single plane, which is defined by the availability of two key substrates. A finite number of qualitatively distinct patterns of metabolic pathway utilization were identified in this plane, dividing it into discrete phases. The characteristics of these distinct phases are interpreted using ratios of shadow prices in the form of isoclines. The isoclines can be used to classify the state of the metabolic network. This methodology gives rise to a "phase plane" analysis of the metabolic genotype-phenotype relation relevant for a range of growth conditions. Phenotype phase planes (PhPPs) were generated for Escherichia coli growth on two carbon sources (acetate and glucose) at all levels of oxygenation, and the resulting optimal metabolic phenotypes were studied. Supplementary information can be downloaded from our website (http://epicurus.che.udel.edu).     

Using overall allele-sharing to detect the presence of large-scale data errors and parameter misspecification in sib-pair linkage studies

Data errors and marker allele frequency misspecification can lead to incorrect inference in linkage analysis. Here we demonstrate the effect of each on an allele-sharing statistic in a sample of sib pairs. In the context of relationship testing, we propose a new test that compares the sample genome-wide sib-pair allele sharing to its expectation and show that this test can detect the presence of large-scale data and model errors.     

Vasoactive and atherogenic effects of cigarette smoking: a study of monozygotic twins discordant for smoking.

The mechanism by which atherosclerotic disease is induced by cigarette smoking has not yet been identified unequivocally. Chronic cigarette smoking and the generation of vasoactive prostanoids and the size of carotid atherosclerotic plaques were studied in nine pairs of identical male twins discordant for smoking for over 20 years. The urinary excretion of 2,3-dinor-thromboxane B2 (thromboxane B2 metabolite) of the smoking twin was significantly higher (on average 1.8 times higher) in every pair and that of 2,3-dinor-6-keto-prostaglandin F1 alpha (prostacyclin metabolite) was significantly higher (on average 1.3 times higher) in eight of the nine pairs. The ratio of excretion of these metabolites was significantly higher, being 4.0 (95% confidence interval 2.7 to 5.4) among the smokers compared with 2.9 (2.1 to 3.8) among the non-smokers, thus favouring a mechanism of vasoconstriction. Excretion of the thromboxane B2 metabolite was related to the urinary concentrations of nicotine metabolites. Atherosclerotic plaques detected by ultrasonography in the carotid arteries were significantly larger among smokers but did not correlate with the urinary excretion of prostacyclin and thromboxane B2 metabolites or intensity of smoking. Smoking was concluded to induce activation of platelets by an effect mediated by nicotine. The increased prostacyclin production, on the other hand, suggested a compensatory mechanism for the general vasoconstrictive properties of cigarette smoking.     

A multivariate method for detecting genetic linkage, with application to a pedigree with an adverse lipoprotein phenotype.

The robust or model-free method for detecting linkage developed by Haseman and Elston for data from sib pairs is extended to incorporate observations of multiple traits on each individual. A method is proposed that estimates the linear function that results in the strongest correlation between the squared pair differences in the trait measurements and identity by descent at a marker locus. The method is illustrated by the study of apolipoprotein and cholesterol levels in individuals from a large family that had many members diagnosed with coronary heart disease.     

Families with familial combined hyperlipidemia and families enriched for coronary artery disease share genetic determinants for the atherogenic lipoprotein phenotype.

Small, dense LDL particles consistently have been associated with hypertriglyceridemia, premature coronary artery disease (CAD), and familial combined hyperlipidemia (FCH). Previously, we have observed linkage of LDL particle size with four separate candidate-gene loci in a study of families enriched for CAD. These loci contain the genes for manganese superoxide dismutase (MnSOD), on chromosome 6q; for apolipoprotein AI-CIII-AIV, on chromosome 11q; for cholesteryl ester transfer protein (CETP) and lecithin:cholesterol acyltransferase (LCAT), on chromosome 16q; and for the LDL receptor (LDLR), on chromosome 19p. We have now tested whether these loci also contribute to LDL particle size in families ascertained for FCH. The members of 18 families (481 individuals) were typed for genetic markers at the four loci, and linkage to LDL particle size was assessed by nonparametric sib-pair linkage analysis. The presence of small, dense LDL (pattern B) was much more frequent in the FCH probands (39%) than in the spouse controls (4%). Evidence for linkage was observed at the MnSOD (P=.02), CETP/LCAT (P=.03), and apolipoprotein AI-CIII-AIV loci (P=.005) but not at the LDLR locus. We conclude that there is a genetically based association between FCH and small, dense LDL and that the genetic determinants for LDL particle size are shared, at least in part, among FCH families and the more general population at risk for CAD.