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L Almasy

Publications and source records attributed to L Almasy.

At least 55 records · Page 3Linked to original sources

Functional effects of the ABO locus polymorphism on plasma levels of von Willebrand factor, factor VIII, and activated partial thromboplastin time.

Lower levels of factor VIII and von Willebrand factor (vWF) have been reported in individuals with blood type O compared with individuals with other ABO blood types. However, this relationship has been demonstrated only by association studies and not by linkage studies. Also, it is not clear whether the ABO locus exerts a functional effect directly on these plasma factors or whether the ABO locus is in linkage disequilibrium with another locus that controls these factors. To distinguish between these 2 possibilities, we applied new statistical methods combining linkage and association tests in a pedigree-based sample. In contrast to most previous studies that used the ABO phenotypes, our study used the ABO genotypes, permitting us to distinguish AO from AA and BO from BB. Our results clearly showed significant linkage between the ABO locus and vWF antigen (P=0.00075). In addition, factor VIII coagulant activity and activated partial thromboplastin time showed suggestive linkage with the ABO locus (P=0.10 and P=0.13). All 3 plasma phenotypes showed significant differences between OO and non-OO genotypes. In addition, vWF antigen exhibited significant differences between O heterozygotes and non-OO homozygotes. This study is unique because it used a combined linkage and association test, which indicated that the ABO locus itself has a functional effect on these plasma phenotypes.

ABO Blood-Group System↗

Quantitative trait locus mapping using human pedigrees.

In the past decade phenomenal progress has been made in molecular and statistical genetic methods for localizing quantitative trait loci. Because of these advances, we can anticipate a long period of active genetic research in which the genes influencing human quantitative variability will be mapped and their effects accurately evaluated. Here, we review the current state of the science in statistical genetic methods for quantitative trait linkage analysis. In particular, we detail a variance component-based framework for localizing quantitative trait loci and for accurately estimating their relative effect sizes. Attention is paid to the optimal design of human family studies for localizing genes of small to moderate effect. In addition, methods and strategies are described for dealing with the most important complications of quantitative variation, including the assessment of genotype x environment interaction and epistasis.

Bias↗

Heritability of event-related brain potentials in families with a history of alcoholism.

Event-related brain potentials (ERPs) are altered in patients with a variety of psychiatric disorders and may represent quantitative correlates of disease liability that are more amenable to genetic analysis than disease status itself. Estimates of heritability are presented for amplitude and latency of the N1 and P3 components of the ERP measured at 19 scalp locations in response to visual and auditory stimuli for 604 individuals in 100 pedigrees ascertained as part of the Collaborative Study on the Genetics of Alcoholism. Significant heritabilities were found for visual P3 amplitude in response to all stimuli and for visual P3 latency in response to target and novel, but not non-target, stimuli. Heritability of visual N1 latencies was uniformly low, whereas heritability of visual N1 amplitude was significant for all electrodes in response to the non-target stimuli but only for posterior electrodes in the other two stimulus conditions. Heritabilities for auditory target P3 were similar to those of the visual stimuli, with auditory target P3 amplitudes and latencies both demonstrating significant heritability. For auditory P2 in response to non-target stimuli, peak amplitude was heritable, but latency was not. Auditory N1 amplitude and latency were significantly heritable for both target and non-target conditions and did not demonstrate the anterior/posterior patterning obtained for visual N1 amplitude. This study represents the first systematic assessment of heritability of these potential neurophysiological markers in families with a history of alcoholism and suggests that many of these ERP phenotypes have heritabilities strong enough to justify genomic screening for loci jointly influencing ERP abnormalities and liability to alcoholism.

Adolescent↗

Quantitative trait linkage mapping in anthropology.

Recent years have seen rapid progress in several areas of both biomedical and anthropological genetics. While genetic analyses have come to play a significant role in biological anthropology, there has been little use of modern methods for linkage mapping of quantitative trait loci (QTLs). It is now feasible to design research studies to investigate the quantitative genetics of complex phenotypes that are of primary importance to traditional questions in biological anthropology. Complex traits such as functionally significant morphological features, physiological characteristics or aspects of behavior can be examined to estimate the influence of genetic variation on within-species phenotypic variation. In addition, new methods for mapping quantitative trait loci provide opportunities to identify the regions within chromosomes that contain the functional genes of interest. This review summarizes molecular genetic and statistical genetic approaches to QTL mapping, and presents examples of how this approach can expand the scope of anthropological genetics to include mapping and identifying individual genes that influence complex phenotypic traits relevant to fundamental questions in biological anthropology.

Animals↗

Exploring genetic analysis of complex traits through the paradigm of alcohol dependence: summary of GAW11 contributions.

We discuss the Genetic Analysis Workshop 11 analyses of data from the Collaborative Study on the Genetics of Alcoholism from a methodological perspective, concentrating on approaches and issues relevant to linkage and association studies of complex human phenotypes. Genome screening by parametric linkage, nonparametric linkage, association, and combined linkage/association methods are discussed. Issues particular to complex disease include etiologic heterogeneity, multivariate phenotype modeling, and parent-of-origin effects. Other methodological topics discussed are new and enhanced methods, ascertainment, weighting of nonindependent sib pairs, and data cleaning and validation.

Alcoholism↗

Quantitative trait locus detection using combined linkage/disequilibrium analysis.

We describe an extension of the variance component linkage method that augments identity-by-descent information from relatives with identity-by-state information from unrelated individuals, exploiting disequilibrium to facilitate fine mapping of quantitative trait loci. An advantage of the combined linkage/disequilibrium test is that it detects association only in the presence of linkage and is not biased by population stratification.

Alcoholism↗

Oligogenic model selection using the Bayesian Information Criterion: linkage analysis of the P300 Cz event-related brain potential.

The traditional likelihood-based approach to hypothesis testing may not be an optimal strategy for evaluating oligogenic models of inheritance. Under oligogenic inheritance the number of possible multilocus models can become very large; there may be several competing linkage models having similar likelihoods; and comparisons among non-nested models can be required to determine if a given multilocus model provides a significantly better fit to observed phenotypic variation than an alternative model. We propose an efficient Bayesian approach to oligogenic model selection that makes use of existing model likelihoods, and show how model uncertainty can be incorporated into parameter estimation.

Alcoholism↗

Genetic analysis of personality traits and alcoholism using a mixed discrete continuous trait variance component model.

Bivariate analyses can improve power to detect linkage. This paper describes one application of a bivariate variance component method for estimating joint likelihoods of a continuous and a discrete trait. This method is applied to the Collaborative Study on the Genetics of Alcoholism data set to investigate the relationship between personality traits derived from the tridimensional personality questionnaire (TPQ) and alcoholism. The results indicate that the novelty-seeking subscale of the TPQ and alcoholism share a strong and significant genetic correlation (rho G = 0.83) and modest environmental correlation (rho E = 0.31). When both traits are considered jointly in a multipoint linkage model compared with the alcoholism trait alone, there is an improvement in the ability to detect and localize a quantitative trait locus on chromosome 4.

Age Factors↗

Smoking behavior is under the influence of a major quantitative trait locus on human chromosome 5q.

Despite some evidence that smoking behavior is influenced by both genetic and environmental factors, efforts at identifying specific genes that influence smoking are extremely limited. Using information on smoking behavior history for 973 individuals distributed across 105 COGA families and a multipoint variance components method, we tested for linkage between smoking behavior (as defined by number of cigarette packs per day for 1 year) and chromosomal locations across the genome using information from 296 markers. We found strong evidence (lod = 3.2) for linkage of smoking behavior to a genetic location on chromosome 5q (D5S1354). Weaker evidence was found for linkage of smoking behavior to genetic locations on chromosomes 4 (between markers D4S244 and D4S2393), 15 (D15S642), and 17 (GATA193). Oligogenic linkage analyses suggest the putative locus on chromosome 5q is the primary determinant of genetic variation in smoking. Although the magnitude of the lod score is compelling, the large gap between the markers D5S1456 and D5S1354 (which is also at the end of chromosome 5q) in the COGA data set reduces the enthusiasm for this putative quantitative trait locus. However, typing of additional markers in this region may provide greater support for the localization of a susceptibility locus at this chromosomal location, which is not far from the DRD1 (D1 dopamine receptor gene) locus.

Chromosomes, Human, Pair 5↗

An empirical test of the significance of an observed quantitative trait locus effect that preserves additive genetic variation.

We propose a constrained permutation test that assesses the significance of an observed quantitative trait locus effect against a background of genetic and environmental variation. Permutations of phenotypes are not selected at random, but rather are chosen in a manner that attempts to maintain the additive genetic variability in phenotypes. Such a constraint maintains the nonindependence among observations under the null hypothesis of no linkage. The empirical distribution of the lod scores calculated using permuted phenotypes is compared to that obtained using phenotypes simulated from the assumed underlying multivariate normal model. We make comparisons of univariate analyses for both a quantitative phenotype that appears consistent with a multivariate normal model and a quantitative phenotype containing pronounced outliers. An example of a bivariate analysis is also presented.

Alcoholism↗

Effects of genotype x sex interaction on linkage analysis of visual event-related evoked potentials.

Autosomal genes contributing to variation in many complex traits are influenced by male or female physiological "environments." Accounting for such genotype-by-sex (G x S) interactions has been shown to be important in quantitative genetic, segregation, and linkage analyses of a number of sexually dimorphic traits. In analyses of data simulated for GAW10, we showed that incorporating sex-specific variance components into a variance components-based linkage method increased the power to detect linkage in a trait that exhibited G x S interaction. The goals of this study of data from the Collaborative Study on the Genetics of Alcoholism (COGA) were to screen the event-related brain potential (ERP) data from COGA participants for G x S interaction, and then to conduct variance components linkage analysis of ERP phenotypes showing evidence of G x S interaction using models incorporating sex-specific variance components. Significant G x S interaction was found in four ERP phenotypes: N100 measured at occipital leads 1 and 2, and P300 measured at occipital leads 1 and 2. In linkage analyses of these traits, the most significant lod score found was that between N100 occipital lead 1 amplitude and marker D7S490. The peak lod score at the D7S490 locus was 2.45 without sex-specific variance components, and 3.25 with sex-specific marker and residual polygenic components.

Alcoholism↗

Linkage of type 2 diabetes mellitus and of age at onset to a genetic location on chromosome 10q in Mexican Americans.

Since little is known about chromosomal locations harboring type 2 diabetes-susceptibility genes, we conducted a genomewide scan for such genes in a Mexican American population. We used data from 27 low-income extended Mexican American pedigrees consisting of 440 individuals for whom genotypic data are available for 379 markers. We used a variance-components technique to conduct multipoint linkage analyses for two phenotypes: type 2 diabetes (a discrete trait) and age at onset of diabetes (a truncated quantitative trait). For the multipoint analyses, a subset of 295 markers was selected on the basis of optimal spacing and informativeness. We found significant evidence that a susceptibility locus near the marker D10S587 on chromosome 10q influences age at onset of diabetes (LOD score 3.75) and is also linked with type 2 diabetes itself (LOD score 2.88). This susceptibility locus explains 63.8%+/-9.9% (P=. 000016) of the total phenotypic variation in age at onset of diabetes and 65.7%+/-10.9% (P=.000135) of the total variation in liability to type 2 diabetes. Weaker evidence was found for linkage of diabetes and of age at onset to regions on chromosomes 3p, 4q, and 9p. In conclusion, our strongest evidence for linkage to both age at onset of diabetes and type 2 diabetes itself in the Mexican American population was for a region on chromosome 10q.

Age Factors↗

Human pedigree-based quantitative-trait-locus mapping: localization of two genes influencing HDL-cholesterol metabolism.

Common disorders with genetic susceptibilities involve the action of multiple genes interacting with each other and with environmental factors, making it difficult to localize the specific genetic loci responsible. An important route to the disentangling of this complex inheritance is through the study of normal physiological variation in quantitative risk factors that may underlie liability to disease. We present an analysis of HDL-cholesterol (HDL-C), which is inversely correlated with risk of heart disease. A variety of HDL subphenotypes were analyzed, including HDL particle-size classes and the concentrations and proportions of esterified and unesterified HDL-C. Results of a complete genomic screen in large, randomly ascertained pedigrees implicated two loci, one on chromosome 8 and the other on chromosome 15, that influence a component of HDL-C-namely, unesterified HDL2a-C. Multivariate analyses of multiple HDL phenotypes and simultaneous multilocus analysis of the quantitative-trait loci identified permit further characterization of the genetic effects on HDL-C. These analyses suggest that the action of the chromosome 8 locus is specific to unesterified cholesterol levels, whereas the chromosome 15 locus appears to influence both HDL-C concentration and distribution of cholesterol among HDL particle sizes.

Adult↗

Joint multipoint linkage analysis of multivariate qualitative and quantitative traits. I. Likelihood formulation and simulation results.

We describe a variance-components method for multipoint linkage analysis that allows joint consideration of a discrete trait and a correlated continuous biological marker (e.g., a disease precursor or associated risk factor) in pedigrees of arbitrary size and complexity. The continuous trait is assumed to be multivariate normally distributed within pedigrees, and the discrete trait is modeled by a threshold process acting on an underlying multivariate normal liability distribution. The liability is allowed to be correlated with the quantitative trait, and the liability and quantitative phenotype may each include covariate effects. Bivariate discrete-continuous observations will be common, but the method easily accommodates qualitative and quantitative phenotypes that are themselves multivariate. Formal likelihood-based tests are described for coincident linkage (i.e., linkage of the traits to distinct quantitative-trait loci [QTLs] that happen to be linked) and pleiotropy (i.e., the same QTL influences both discrete-trait status and the correlated continuous phenotype). The properties of the method are demonstrated by use of simulated data from Genetic Analysis Workshop 10. In a companion paper, the method is applied to data from the Collaborative Study on the Genetics of Alcoholism, in a bivariate linkage analysis of alcoholism diagnoses and P300 amplitude of event-related brain potentials.

Chromosome Mapping↗

Joint multipoint linkage analysis of multivariate qualitative and quantitative traits. II. Alcoholism and event-related potentials.

The availability of robust quantitative biological markers that are correlated with qualitative psychiatric phenotypes can potentially improve the power of linkage methods to detect quantitative-trait loci influencing psychiatric disorders. We apply a variance-component method for joint multipoint linkage analysis of multivariate discrete and continuous traits to the extended pedigree data from the Collaborative Study on the Genetics of Alcoholism, in a bivariate analysis of qualitative alcoholism phenotypes and quantitative event-related potentials. Joint consideration of the DSM-IV diagnosis of alcoholism and the amplitude of the P300 component of the Cz event-related potential significantly increases the evidence for linkage of these traits to a chromosome 4 region near the class I alcohol dehydrogenase locus ADH3. A likelihood-ratio test for complete pleiotropy is significant, suggesting that the same quantitative-trait locus influences both risk of alcoholism and the amplitude of the P300 component.

Alcohol Dehydrogenase↗

A genome search identifies major quantitative trait loci on human chromosomes 3 and 4 that influence cholesterol concentrations in small LDL particles.

Small, dense LDL particles are associated with increased risk of cardiovascular disease. To identify the genes that influence LDL size variation, we performed a genome-wide screen for cholesterol concentrations in 4 LDL size fractions. Samples from 470 members of randomly ascertained families were typed for 331 microsatellite markers spaced at approximately 15 cM intervals. Plasma LDLs were resolved by using nondenaturing gradient gel electrophoresis into 4 fraction sizes (LDL-1, 26.4 to 29.0 nm; LDL-2, 25.5 to 26.4 nm; LDL-3, 24.2 to 25.5 nm; and LDL-4, 21.0 to 24.2 nm) and cholesterol concentrations were estimated by staining with Sudan Black B. Linkage analyses used variance component methods that exploited all of the genotypic and phenotypic information in the large extended pedigrees. In multipoint linkage analyses with quantitative trait loci for the 4 fraction sizes, only LDL-3, a fraction containing small LDL particles, gave peak multipoint log10 odds in favor of linkage (LOD) scores that exceeded 3.0, a nominal criterion for evidence of significant linkage. The highest LOD scores for LDL-3 were found on chromosomes 3 (LOD=4.1), 4 (LOD=4.1), and 6 (LOD=2.9). In oligogenic analyses, the 2-locus LOD score (for chromosomes 3 and 4) increased significantly (P=0.0012) to 6.1, but including the third locus on chromosome 6 did not significantly improve the LOD score (P=0.064). Thus, we have localized 2 major quantitative trait loci that influence variation in cholesterol concentrations of small LDL particles. The 2 quantitative trait loci on chromosomes 3 and 4 are located in regions that contain the genes for apoD and the large subunit of the microsomal triglyceride transfer protein, respectively.

Adolescent↗

Normal variation in leptin levels in associated with polymorphisms in the proopiomelanocortin gene, POMC.

We previously reported that our genome-scanning initiative had detected a highly significant linkage (log odds ratio = 4.95; P = 9 x 10(-7)) between a quantitative trait locus (QTL) on chromosome 2 and leptin levels in Mexican American families. We now have typed additional microsatellite markers in this region, increasing this log odds ratio score to 7.46 (P = 2 x 10(-9)). This region of chromosome 2 contains a strong positional candidate gene, POMC. The POMC gene codes for POMC, the prohormone from which alphaMSH, ACTH, and beta-endorphin are derived. Studies by others have shown that POMC-derived products are involved in the regulation of appetite and obesity. We have used polymorphisms in POMC to map its location within the 95% confidence interval of the peak for the linkage signal for the QTL. We also constructed POMC haplotypes using these polymorphisms and have found a significant association with normal variation in leptin levels (P = 0.001). We conclude that variation in POMC is associated with normal variation in serum leptin levels, providing further evidence that POMC may be the leptin QTL previously identified in Mexican American families.

Chromosome Mapping↗