Biomedical subjects

T D Dyer

Publications and source records attributed to T D Dyer.

At least 19 recordsLinked to original sources

PubMed2006

Identification of two novel quantitative trait loci for pre-eclampsia susceptibility on chromosomes 5q and 13q using a variance components-based linkage approach.

Pre-eclampsia/eclampsia (PE/E) is a common and serious disorder of human pregnancy that is associated with substantial maternal and perinatal morbidity and mortality. The suspected aetiology of PE/E is complex, with susceptibility being attributable to multiple environmental factors and a large genetic component. By assuming that the underlying liability towards PE/E susceptibility is inherently quantitative, any PE/E susceptibility gene would represent a quantitative trait locus (QTL). This assumption enables a more refined and powerful variance components procedure using a threshold model for our PE/E statistical analysis. Using this more efficient linkage approach, we have now re-analysed our previously completed Australian/New Zealand genome scan data to identify two novel PE/E susceptibility QTLs on chromosomes 5q and 13q. We have obtained strong evidence of linkage on 5q with a peak logarithm-of-odds (LOD) score of 3.12 between D5S644 and D5S433 [at approximately 121 centimorgan (cM)] and strong evidence of linkage on 13q with a peak LOD score of 3.10 between D13S1265 and D13S173 (at approximately 123 cM). Objective identification and prioritization of positional candidate genes using the quantitative bioinformatics program GeneSniffer revealed highly plausible PE/E candidate genes encoding aminopeptidase enzymes and a placental peptide hormone on the 5q QTL and two type IV collagens on the 13q QTL regions, respectively.

Analysis of Variance↗

PubMed2006

Association between variants in the genes for adiponectin and its receptors with insulin resistance syndrome (IRS)-related phenotypes in Mexican Americans.

AIMS/HYPOTHESIS: The aim of this study was to examine whether genetic variation in ADIPOQ, ADIPOR1 and ADIPOR2 may contribute to increased susceptibility to components of the insulin resistance syndrome (IRS). MATERIALS AND METHODS: We genotyped single-nucleotide polymorphisms (SNPs) in ADIPOQ, ADIPOR1 and ADIPOR2 in Mexican American subjects (N=439) and performed an association analysis of IRS-related traits. RESULTS: Of the eight SNPs examined in the ADIPOQ gene, rs4632532 and rs182052 exhibited significant associations with BMI (p=0.029 and p=0.032), fasting specific insulin (p=0.023 and p=0.026), sum of skin folds (SS) (p=0.0089 and p=0.0084) and homeostasis model assessment of insulin sensitivity (HOMA-%S) (p=0.015 and p=0.016). Two other SNPs, rs266729 and rs2241767, were significantly associated with SS (p=0.036 and p=0.013). SNP rs7539542 of ADIPOR1 was significantly associated with BMI, SS and waist circumference (p=0.025, p=0.047 and p=0.0062). Fourteen of the ADIPOR2 SNPs were found to be significantly (p<0.05) associated with fasting plasma triglyceride concentrations. Four of these SNPs (rs10848569, rs929434, rs3809266 and rs12342) were in high pairwise linkage disequilibrium (r (2)=0.99) and were strongly associated with fasting triglyceride levels (p=0.00029, p=0.00016, p=0.00027 and p=0.00021). Adjusting for the effects of BMI and HOMA-%S on triglyceride concentrations increased significance to p=0.000060 for SNP rs929434. Bayesian quantitative trait nucleotide analysis was used to examine all possible models of gene action. Again, SNP rs929434 provided the strongest statistical evidence of an effect on triglyceride concentrations. CONCLUSIONS/INTERPRETATION: These results provide evidence for association of SNPs in ADIPOQ and its receptors with multiple IRS-related phenotypes. Specifically, several genetic variants in ADIPOR2 were strongly associated with decreased triglyceride levels.

Adiponectin↗

PubMed2006

Objective prioritization of positional candidate genes at a quantitative trait locus for pre-eclampsia on 2q22.

Pre-eclampsia/eclampsia (PE/E) is a common, serious medical disorder of human pregnancy. Familial association of PE/E has been recognized for decades, but the genetics are complex and poorly understood. In an attempt to identify PE/E susceptibility genes, we embarked on a positional cloning strategy using 34 Australian and New Zealand PE/E pedigrees. An initial 10-cM resolution genome scan revealed a putative susceptibility locus spanning a broad region on chromosome 2 that overlaps an independently determined linkage signal seen in Icelandic PE pedigrees. Subsequent fine mapping using 25 additional short tandem repeat (STR) markers in this region and non-parametric multipoint linkage analysis did not change the overall position. Under a strict diagnosis of PE, we obtained significant evidence of linkage on 2q with a peak log-of-odds ratio score (LOD) of 3.43 near marker D2S151 at 155 cM. To prioritize positional candidate genes at the 2q locus for detailed analysis, we applied an objective prioritization strategy that integrates quantitative bioinformatics, assessment of differential gene expression and association analysis of single-nucleotide polymorphisms (SNPs). Highest priority was assigned to the activin receptor gene ACVR2. This gene also showed >10-fold differential gene expression in human decidual tissue from normotensive and PE individuals. We genotyped five known SNPs in this gene in our pedigrees and performed tests for association and linkage disequilibrium. One SNP (rs1424954) showed strong preliminary evidence of association with PE (P = 0.007), whereas two others (rs1364658 and rs1895694) exhibited nominal evidence (P < 0.05). Haplotype analysis revealed no additional association information. There was evidence of weak linkage disequilibrium among these SNPs. The highest observed LD occurred between the two strongest associated SNPs, suggesting that the observed signals may be the signature of an observed functional variant.

Activin Receptors, Type II↗

PubMed2006

A locus on chromosome 13 influences levels of TAFI antigen in healthy Mexican Americans.

When activated, thrombin activatable fibrinolysis inhibitor (TAFI) inhibits fibrinolysis by modifying fibrin, depressing its plasminogen binding potential. Polymorphisms in the TAFI structural gene (CPB2) have been associated with variation in TAFI levels, but the potential occurrence of influential quantitative trait loci (QTLs) located elsewhere in the genome has been explored only in families ascertained in part through probands affected by thrombosis. We report the results of the first genome-wide linkage screen for QTLs that influence TAFI phenotypes. Data are from 635 subjects from 21 randomly ascertained Mexican American families participating in the San Antonio Family Heart Study. Potential QTLs were localized through a genome-wide multipoint linkage scan using 417 highly informative autosomal short tandem repeat markers spaced at approximately 10-cM intervals. We observed a maximum multipoint LOD score of 3.09 on chromosome 13q, the region of the TAFI structural gene. A suggestive linkage signal (LOD = 2.04) also was observed in this region, but may be an artifact. In addition, weak evidence for linkage occurred on chromosomes 17p and 9q. Our results suggest that polymorphisms in the TAFI structural gene or its nearby regulatory elements may contribute strongly to TAFI level variation in the general population, although several genes in other regions of the genome may also influence variation in this phenotype. Our findings support those of the Genetic Analysis of Idiopathic Thrombophilia (GAIT) project, which identified a potential TAFI QTL on chromosome 13q in a genome-wide linkage scan in Spanish thrombophilia families.

Adult↗

PubMed2005

Genotype-by-sex interaction in the regulation of high-density lipoprotein: the Framingham Heart Study.

Low levels of high-density lipoprotein (HDL) are widely documented as a risk factor for cardiovascular disease (CVD). Furthermore, there is marked sexual dimorphism in both HDL levels and the prevalence of CVD. However, the extent to which genetic factors contribute to such dimorphism has been largely unexplored. We examined the evidence for genotype-by-sex effects on HDL in a longitudinal sample of 1562 participants from 330 families in the Framingham Heart Study at three times points corresponding approximately to 1971-1974, 1980-1983, and 1988-1991. Using a variance component method, we conducted a genome scan of HDL at each time point in males and females, separately and combined, and tested for genotype-by-sex interaction at a quantitative trait locus (QTL) at each time point. Consistent findings were noted only for females on chromosome 2 near marker D2S1328, with adjusted LOD scores of 2.6, 2.2, and 2.1 across the three time points, respectively. In males suggestive linkage was detected on chromosome 16 near marker D16S3396 at the second time point and on chromosome 18 near marker D18S851 at the third time point (adjusted LOD = 2.2 and 2.4, respectively). Although the heritability of HDL is similar in males and females, sex appears to exert a substantial effect on the QTL-specific variance of HDL. When genotype-by-sex interactions exist and are not modeled, the power to detect linkage is reduced; thus our results may explain in part the paucity of significant linkage findings for HDL.

Adult↗

PubMed2001

A major locus for fasting insulin concentrations and insulin resistance on chromosome 6q with strong pleiotropic effects on obesity-related phenotypes in nondiabetic Mexican Americans.

Insulin resistance and hyperinsulinemia are strong correlates of obesity and type 2 diabetes, but little is known about their genetic determinants. Using data on nondiabetics from Mexican American families and a multipoint linkage approach, we scanned the genome and identified a major locus near marker D6S403 for fasting "true" insulin levels (LOD score 4.1, empirical P<.0001), which do not crossreact with insulin precursors. Insulin resistance, as assessed by the homeostasis model using fasting glucose and specific insulin (FSI) values, was also strongly linked (LOD score 3.5, empirical P<.0001) with this region. Two other regions across the genome were found to be suggestively linked to FSI: a location on chromosome 2q, near marker D2S141, and another location on chromosome 6q, near marker D6S264. Since several insulin-resistance syndrome (IRS)-related phenotypes were mapped independently to the regions on chromosome 6q, we conducted bivariate multipoint linkage analyses to map the correlated IRS phenotypes. These analyses implicated the same chromosomal region near marker D6S403 (6q22-q23) as harboring a major gene with strong pleiotropic effects on obesity and on lipid measures, including leptin concentrations (e.g., LOD(eq) for traits-specific insulin and leptin was 4.7). A positional candidate gene for insulin resistance in this chromosomal region is the plasma cell-membrane glycoprotein PC-1 (6q22-q23). The genetic location on chromosome 6q, near marker D6S264 (6q25.2-q26), was also identified by the bivariate analysis as exerting significant pleiotropic influences on IRS-related phenotypes (e.g., LOD(eq) for traits-specific insulin and leptin was 4.1). This chromosomal region harbors positional candidate genes, such as the insulin-like growth factor 2 receptor (IGF2R, 6q26) and acetyl-CoA acetyltransferase 2 (ACAT2, 6q25.3-q26). In sum, we found substantial evidence for susceptibility loci on chromosome 6q that influence insulin concentrations and other IRS-related phenotypes in Mexican Americans.

Adult↗

PubMed2001

The effect of pedigree complexity on quantitative trait linkage analysis.

Due to the computational difficulties of performing linkage analysis on large complex pedigrees, most investigators resort to simplifying such pedigrees by some ad hoc strategy. In this paper, we suggest an analytical method to compare the power of various pedigree simplification schemes by using the asymptotic distribution of the likelihood-ratio statistic. We applied the method to the large Hutterine pedigree. Our results indicate that the breaking and reduction of inbreeding loops can greatly diminish the power to localize quantitative trait loci. We also present an efficient Monte Carlo method for estimating identity-by-descent allele sharing in large complex pedigrees. This method is used to facilitate a linkage analysis of serum IgE levels in the Hutterites without simplifying the pedigree.

Adult↗

PubMed2001

GAW12: simulated genome scan, sequence, and family data for a common disease.

The Genetic Analysis Workshop (GAW) 12 simulated data involves a common disease defined by imposing a threshold on a quantitative liability distribution. Associated with the disease are five quantitative risk factors, a quantitative environmental exposure, and a dichotomous environmental variable. Age at disease onset and household membership were also simulated. Genotype data, including 2,855 microsatellites on 22 autosomes, were simulated for 1,497 individuals in 23 families. Phenotype data and sequence data for seven candidate genes were provided for 1,000 of these individuals who were "living" and available for study. Data were simulated for 50 replicate samples in each of two populations, a general population and a population isolate formed from a small group of founders.

Adolescent↗

PubMed2000

A major susceptibility locus influencing plasma triglyceride concentrations is located on chromosome 15q in Mexican Americans.

Although several genetic forms of rare or syndromic hypertriglyceridemia have been reported, little is known about the specific chromosomal regions across the genome harboring susceptibility genes for common forms of hypertriglyceridemia. Therefore, we conducted a genomewide scan for susceptibility genes influencing plasma triglyceride (TG) levels in a Mexican American population. We used both phenotypic and genotypic data from 418 individuals distributed across 27 low-income, extended Mexican American families. For the analyses, TG values were log transformed (ln TG). We used a variance-components technique to conduct multipoint linkage analyses for localizing susceptibility genes that determine variation in TG levels. We used an approximately 10-15-cM map, which was made on the basis of information from 295 microsatellite markers. After accounting for the effects of sex and sex-specific age terms, we found significant evidence for linkage (LOD = 3.88) of ln TG levels to a genetic location between the markers GABRB3 and D15S165 on chromosome 15q. This putative locus explains 39.7+/-7% (P=.000012) of total phenotypic variation in ln TG levels. Suggestive evidence was found for linkage of ln TG levels to two different locations on chromosome 7, which are approximately 85 cM apart from each other. Also, there is some evidence for linkage of high-density lipoprotein cholesterol concentrations to a genetic location near one of the regions on chromosome 7. In conclusion, we found strong evidence for linkage of ln TG levels to a genetic location on chromosome 15q in a Mexican American population, which is prone to disease conditions such as type 2 diabetes and the insulin-resistance syndrome that are associated with hypertriglyceridemia. This putative locus appears to have a major influence on ln TG variation.

Adult↗

PubMed1999

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↗

PubMed1999

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↗

PubMed1999

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↗

PubMed1997

GAW10: simulated family data for a common oligogenic disease with quantitative risk factors.

GAW10 Problem 2 involves a simulated common disease defined by imposing a threshold, T, on a quantitative trait, Q1. Every individual with a value of Q1 > or = T (where T = 40) is defined as affected. Also thought to be associated with the disease as intervening variables are four other quantitative traits (Q2, Q3, Q4, and Q5) and an environmental factor (EF). Each individual has genotypes for 367 highly polymorphic markers on 10 chromosomes. The tasks for GAW10 were to characterize the genetic and environmental contribution to Q1 (and the disease), Q2, Q3, Q4, and Q5, and to localize any single genes that have detectable effects. Multiple replicates provided an opportunity to address questions of power and false positive rates.

Chromosome Mapping↗

PubMed1997

Bivariate quantitative trait linkage analysis: pleiotropy versus co-incident linkages.

Power to detect linkage and localization of a major gene were compared in univariate and bivariate variance components linkage analysis of three related quantitative traits in general pedigrees. Although both methods demonstrated adequate power to detect loci of moderate effect, bivariate analysis improved both power and localization for correlated quantitative traits mapping to the same chromosomal region, regardless of whether co-localization was the result of pleiotropy. Additionally, a test of pleiotropy versus co-incident linkage was shown to have adequate power and a low error rate.

Chromosome Mapping↗

PubMed1997

Exploiting pleiotropy to map genes for oligogenic phenotypes using extended pedigree data.

We investigated the utility of two approaches for exploiting pleiotropy to search for genes influencing related traits. To do this we first assessed the genetic correlations among a set of five closely related quantitative traits (Q1, Q2, Q3, Q4, Q5). We then used the genetic correlations among these five traits both to remove the common genetic effects of the four remaining traits, thereby identifying the unique genetic contribution to each trait, and to extract a synthetic phenotype which exploits the shared genetic information (pleiotropy) among these five traits. After obtaining these conditional traits, we then searched for evidence of quantitative trait loci (QTLs) (using variance component linkage) influencing the unique residual genetic component for each trait as well as those influencing the expression of the synthetic traits. From this work, we conclude that the removal of the common genetic effects of other traits in a group may be of greater utility when the majority of the pleiotropy initially detected between traits is attributable to the shared additive effects of polygenes, rather than to those of major loci. By contrast, decomposition of the genetic covariance matrix to its principal components is a greater utility when the majority of pleiotropy is attributable to major loci.

Chromosome Mapping↗

PubMed1997

A major quantitative trait locus determining serum leptin levels and fat mass is located on human chromosome 2.

Obesity is a major predisposing factor for the development of several chronic diseases including non-insulin dependent diabetes mellitus (NIDDM) and coronary heart disease (CHD). Leptin is a serum protein which is secreted by adipocytes and thought to play a role in the regulation of body fat. Leptin levels in humans have been found to be highly correlated with an individual's total adiposity. We performed a genome-wide scan and conducted multipoint linkage analysis using a general pedigree-based variance component approach to identify genes with measurable effects on quantitative variation in leptin levels in Mexican Americans. A microsatellite polymorphism, D2S1788, mapped to chromosome 2p21 (approximately 74 cM from the tip of the short arm) and showed strong evidence of linkage with serum leptin levels with a lod score of 4.95 (P = 9 x 10(-7)). This locus accounted for 47% of the variation in serum leptin levels, with a residual additive genetic component contributing an additional 24%. This region contains several potential candidate genes for obesity, including glucokinase regulatory protein (GCKR) and pro-opiomelanocortin (POMC). Our results show strong evidence of linkage of this region of chromosome 2 with serum leptin levels and indicate that this region could contain an important human obesity gene.

Adipose Tissue↗

PubMed1997

Characterization of a composite gradient gel for the electrophoretic separation of lipoproteins.

We describe a protocol for making a new type of gradient gel, the Composite gradient gel, that was designed to resolve plasma lipoproteins using nondenaturing gradient gel electrophoresis. The new gel format allows analysis both of high density lipoproteins (HDLs) and low density lipoproteins (LDLs) on the same gel. The gel gave highly repeatable (r2 = 0.999) size estimates. We compared lipoprotein phenotypes determined from the new gradient gel with those obtained using specialized HDL and LDL gradient gels. The comparisons indicated that the Composite gel gave lipoprotein particle size estimates for HDLs and LDLs that were virtually identical to those obtained, respectively, from the specialized HDL and LDL gradient gels. We measured median diameters, which reflect the distributions of absorbance, for LDLs and for HDLs and found that the Composite gel gave lipoprotein size distributions that were virtually identical to those measured using the specialized LDL and HDL gels. Finally, comparison of fractional absorbance for six lipoprotein size intervals obtained from the Composite and specialized gels revealed a close correlation (r2 = 0.828). Thus, it appears that both LDL and HDL size phenotypes may be evaluated simultaneously using a single gradient gel format.

Animals↗

PubMed1995

Simulation of a common oligogenic disease with quantitative risk factors. GAW9 problem 2: the answers.

For Problem 2, simulated family data were provided for a common oligogenic disease that was defined by imposing a threshold, T, on a quantitative trait, Q1. Every individual with a value of Q1 > T (where T = 87.5) was defined as affected. Participants were told that three other quantitative traits (Q2, Q3, and Q4) and an environmental factor (EF) also were thought to be associated with the disease as intervening variables, and that 12 candidate loci (C1 - C12) were postulated to influence traits associated with the disease. The tasks for GAW9 were to characterize the genetic and environmental contribution to Q1 (and the disease), Q2, Q3, and Q4, and to localize any single genes that had detectable effects.

Adolescent↗