Biomedical subjects

S C Heath

Publications and source records attributed to S C Heath.

At least 19 recordsLinked to original sources

PubMed2004

Genomic analysis of Fas and FasL genes and absence of correlation with disease progression in AIDS.

Apoptosis has been suggested as a major mechanism for the CD4(+) T-lymphocyte depletion observed in patients infected with human immunodeficiency virus 1 (HIV-1). To evaluate the impact of genetic variations to apoptosis during progression of acquired immunodeficiency syndrome (AIDS), we have performed an extensive genetic analysis of Fas and Fas ligand ( FasL) genes. The coding regions and promoters of these genes were resequenced in a cohort of 212 HIV-1-seropositive patients presenting extreme disease phenotypes and 155 healthy controls of Caucasian origin. Overall, 33 single nucleotide polymorphisms (SNPs) with an allele frequency >1% were identified and evaluated for their association with disease progression. Among them, 14 polymorphisms were newly characterized. We did not find any statistically significant association of Fas and FasL polymorphisms and haplotypes with AIDS progression.

Acquired Immunodeficiency Syndrome↗

PubMed2003

Genomic analysis of Th1-Th2 cytokine genes in an AIDS cohort: identification of IL4 and IL10 haplotypes associated with the disease progression.

Polymorphisms of Th1-Th2 cytokine genes have previously been implicated in the rate of progression to AIDS in seropositive patients. To evaluate further the impact of these genes in the development of AIDS, we have performed an extensive genetic analysis of IL2, IL4, IL6, IL10, IL12p35 and p40, IL13 and IFNgamma. The coding regions and promoters of these genes were sequenced in a Caucasian cohort of 337 HIV-1 seropositive extreme patients (the GRIV cohort) consisting of patients with slow progression and rapid progression, and up to 470 healthy controls. In all, 64 single nucleotide polymorphisms (SNPs) and four deleterious polymorphisms with frequency >1% were identified and evaluated for their association with disease. Statistically significant associations were observed with haplotypes of the IL4 and IL10 genes, but no relation was found with variants of other genes. The catalogue of SNP and haplotypes presented here will facilitate further genetic investigations of Th1-Th2 cytokines in AIDS and other immune-related disorders.

Acquired Immunodeficiency Syndrome↗

PubMed2003

Genome-wide scan in a large complex pedigree with predominantly male schizophrenics from the island of Kosrae: evidence for linkage to chromosome 2q.

It is widely accepted that founder populations hold promise for mapping loci for complex traits. However, the outcome of these mapping efforts will most likely depend on the individual demographic characteristics and historical circumstances surrounding the founding of a given genetic isolate. The 'ideal' features of a founder population are currently unknown. The Micronesian islandic population of Kosrae, one of the four islands comprising the Federated States of Micronesia (FSM), was founded by a small number of settlers and went through a secondary genetic 'bottleneck' in the mid-19th century. The potential for reduced etiological (genetic and environmental) heterogeneity, as well as the opportunity to ascertain extended and statistically powerful pedigrees makes the Kosraen population attractive for mapping schizophrenia susceptibility genes. Our exhaustive case ascertainment from this islandic population identified 32 patients who met DSM-IV criteria for schizophrenia or schizoaffective disorder. Three of these were siblings in one nuclear family, and 27 were from a single large and complex schizophrenia kindred that includes a total of 251 individuals. One of the most startling findings in our ascertained sample was the great difference in male and female disease rates. A genome-wide scan provided initial suggestive evidence for linkage to markers on chromosomes 1, 2, 3, 7, 13, 15, 19, and X. Follow-up multipoint analyses gave additional support for a region on 2q37 that includes a schizophrenia locus previously identified in another small genetic isolate, with a well-established recent genealogical history and a small number of founders, located on the eastern border of Finland. In addition to providing further support for a schizophrenia susceptibility locus at 2q37, our results highlight the analytic challenges associated with extremely large and complex pedigrees, as well as the limitations associated with genetic studies of complex traits in small islandic populations.

Adolescent↗

PubMed2001

A transmission/disequilibrium test that allows for genotyping errors in the analysis of single-nucleotide polymorphism data.

The present study assesses the effects of genotyping errors on the type I error rate of a particular transmission/disequilibrium test (TDT(std)), which assumes that data are errorless, and introduces a new transmission/disequilibrium test (TDT(ae)) that allows for random genotyping errors. We evaluate the type I error rate and power of the TDT(ae) under a variety of simulations and perform a power comparison between the TDT(std) and the TDT(ae), for errorless data. Both the TDT(std) and the TDT(ae) statistics are computed as two times a log-likelihood difference, and both are asymptotically distributed as chi(2) with 1 df. Genotype data for trios are simulated under a null hypothesis and under an alternative (power) hypothesis. For each simulation, errors are introduced randomly via a computer algorithm with different probabilities (called "allelic error rates"). The TDT(std) statistic is computed on all trios that show Mendelian consistency, whereas the TDT(ae) statistic is computed on all trios. The results indicate that TDT(std) shows a significant increase in type I error when applied to data in which inconsistent trios are removed. This type I error increases both with an increase in sample size and with an increase in the allelic error rates. TDT(ae) always maintains correct type I error rates for the simulations considered. Factors affecting the power of the TDT(ae) are discussed. Finally, the power of TDT(std) is at least that of TDT(ae) for simulations with errorless data. Because data are rarely error free, we recommend that researchers use methods, such as the TDT(ae), that allow for errors in genotype data.

Alleles↗

PubMed2001

Genome scans for Q1 and Q2 on general population replicates using Loki.

The Markov Chain Monte Carlo linkage package Loki was used to perform a genome scan under realistic conditions (using a 10-cM marker map without marker data on unsampled individuals, analyzing each chromosome separately, and without knowing the answers) for traits Q1 and Q2 on general population replicate 1. Using this approach we detected and correctly localized MG1 for Q1 and MG3 for Q2. We then repeated the analyses on replicate 1 and the "best replicate" (42) adding more information (using marker data on everyone, fitting a polygenic effect, and analyzing multiple chromosomes jointly) to see the effect on the detection of trait loci. We found that adding more data often improves the quality of the linkage signal, and reduces the false positive rate, but did not allow the detection of trait loci missed by the initial analysis. We also investigated the convergence of the sampler by repeating one multi-chromosome analysis six times with different random number seeds. We concluded that a strategy of performing a single chromosome scan using a moderate number of sampling iterations, followed by a multi-chromosome analysis of all chromosomes with linkage signals detected in the first scan using a longer sampling run, was an effective way of performing a genome scan on this data set.

Chromosome Mapping↗

PubMed2001

Epidemiology and factor analysis of obesity, type II diabetes, hypertension, and dyslipidemia (syndrome X) on the Island of Kosrae, Federated States of Micronesia.

OBJECTIVES: Obesity, type II diabetes, hypertension, and dyslipidemia are major causes of morbidity and mortality throughout the world. Though these disorders often cluster in individuals and families and are collectively known as syndrome X, the basis for this aggregation is not well understood. To further understand the pathogenesis of syndrome X, a comprehensive epidemiological study was undertaken on the Pacific Island of Kosrae, Federated States of Micronesia (FSM). METHODS: The entire adult (>20 years of age) population of Kosrae underwent a clinical evaluation that included a questionnaire that noted the participants' sex, family data including listing of biological parents, siblings, and children, smoking status, village of residence, age and health status. The medical evaluation included: anthropometric measures (weight, height, waist, hip), serum chemistries (leptin, fasting blood sugar (FBS), insulin, total cholesterol (TC), triglycerides (TG), and apolipoproteins B and A-I (apo B and apo A-I) and blood pressure (BP) measurements. RESULTS: Obesity (BMI >/=35) was found in 24%, diabetes (FBS >/=126 or 2-hour oral glucose tolerance test >/=200) in 12%, hypertension (SBP >/=140 or DBP >/=90) in 17%, and dyslipidemia (TC >/=240 or TG >/=200 or apo B >/=120 or apo A-I </=88) in 20% of the population. Significant covariate effects after multivariate analysis were as follows: sex affected the frequency of all four disorders, parity affected the frequency of dyslipidemia, smoking affected the frequency of obesity and diabetes, village of residence affected the frequency of obesity, hypertension, and dyslipidemia, and age affected the frequency of all four disorders. Factor analysis identified four independent factors that explained 73% of the total variance of the entire data set: factor 1 (weight, waist, leptin, insulin, and TG), factor 2 (TC, TG, apo B, apo A-I, and insulin), factor 3 (systolic and diastolic BP, FBS, waist and weight), and factor 4 (apo A-I, TG, leptin, and weight). CONCLUSIONS: This population-based study on the Island of Kosrae suggests that syndrome X is a composite of 4 independent factors: obesity with diabetes and hypertriglyceridemia, combined hyperlipidemia with diabetes, hypertension with obesity and diabetes, and increased HDL-low TG with thinness and high leptin. Further studies to identify the genetic components of these factors as well as the individual traits are under way.

Adult↗

PubMed2000

A cholesterol-lowering gene maps to chromosome 13q.

A cholesterol-lowering gene has been postulated from familial hypercholesterolemia (FH) families having heterozygous persons with normal LDL levels and homozygous individuals with LDL levels similar to those in persons with heterozygous FH. We studied such a family with FH that also had members without FH and with lower-than-normal LDL levels. We performed linkage analyses and identified a locus at 13q, defined by markers D13S156 and D13S158. FASTLINK and GENEHUNTER yielded LOD scores >5 and >4, respectively, whereas an affected-sib-pair analysis gave a peak multipoint LOD score of 4.8, corresponding to a P value of 1.26x10-6. A multipoint quantitative-trait-locus (QTL) linkage analysis with maximum-likelihood binomial QTL verified this locus as a QTL for LDL levels. To test the relevance of this QTL in an independent normal population, we studied MZ and DZ twin subjects. An MZ-DZ comparison confirmed genetic variance with regard to lipid concentrations. We then performed an identity-by-descent linkage analysis on the DZ twins, with markers at the 13q locus. We found strong evidence for linkage at this locus with LDL (P<.0002), HDL (P<.004), total cholesterol (P<.0002), and body-mass index (P<.0001). These data provide support for the existence of a new gene influencing lipid concentrations in humans.

Adult↗

PubMed2000

An analytic solution to single nucleotide polymorphism error-detection rates in nuclear families: implications for study design.

Recently, there has been increased interest in using Single Nucleotide Polymorphisms (SNPs) as a method for detecting genes for complex traits. SNPs are diallelic markers that have the potential to be inexpensively produced using chip technology. It has been suggested that SNPs will be beneficial in study designs that utilize trio data (father, mother, child). In our previous work, we calculated the probability of detecting Mendelian errors at a SNP locus for a trio randomly selected from a population in Hardy-Weinberg equilibrium. The highest error-detection rate was 30%. Here we investigate the error-detection rate when additional sibs are genotyped. We define an error to be a change from a 1 allele to a 2 allele, or vice versa. Typing one additional sib increases the detection rate on average by 10-13%. Typing two additional sibs increases the detection rate on average by 14-19%. The increase in the detection rate is dependent on the allele frequencies. Equal allele frequencies produce the lowest detection rates, independent of true error rates and number of offspring genotyped. Typing additional siblings not only improves error-detection rates, but can also provide additional linkage information. In order to increase linkage information and error-detection rates, at least two additional siblings should be ascertained when available.

Alleles↗

PubMed1999

Distribution of alleles of the methylenetetrahydrofolate reductase (MTHFR) C677T gene polymorphism in familial spina bifida.

Spina bifida cystica (SB) is one of the most common and disabling of birth defects. Folic acid supplementation in mothers during the periconceptional period has been shown to prevent more than 70% of neural tube defects (NTD) including SB. However, the mechanism is unknown. We tested a series of multicase SB families in which 224 individuals were genotyped and a group of 215 unrelated unaffected (external) control individuals for association of SB with the T allele of methylenetetrahydrofolate reductase (MTHFR) C677T polymorphism that produces a heat-labile enzyme protein. The data were analyzed using first the transmission/disequilibrium test (TDT) and second a modified case-control study design with Monte Carlo sampling methods. No association of SB with the MTHFR T allele was found by either method. Presently, association between SB and the T allele has been found in four studies, a Dutch study, an Irish study, a North American study, and an Italian study. But no association was found in four other studies, a British study, a French study, a Turkish study, and a German study. A California population-based study found only modestly increased risk of SB with this allele that was not significant at the P < 0.05 level. The present study finds no evidence of the association. Only one other study, the German study, has used TDT analysis. The present study is the first to use a modified case-control study design with Monte Carlo sampling methods to test this association. Thus, it appears that the MTHFR T allele is a risk factor for SB in some populations but not others. Major genetic risk factors for folate-related SB remain to be found.

Alleles↗

PubMed1999

Searching for alcoholism susceptibility genes using Markov chain Monte Carlo methods.

Markov chain Monte Carlo (MCMC) methods offer a rapid parametric approach that can test for linkage throughout the entire genome. It has an advantage similar to nonparametric methods in that the model does not have to be completely specified a priori. However, unlike nonparametric methods, there are no limitations on pedigree size and MCMC methods can also handle relatively complex pedigree structures. In addition MCMC methods can be used to carry segregation analysis in order to answer questions on the genetic components of a disease phenotype. Segregation analysis gave evidence for between two and eight alcoholism susceptibility loci, each having a modest effect on the phenotype. MCMC methods were used to map alcoholism loci using the phenotypes ALDX1 (DSM-III-R and Feighner criteria) and ALDX2 (World Health Organization diagnosis ICD-10 criteria). There was mild evidence for quantitative trait loci on chromosomes 2, 10, and 11.

Adolescent↗

PubMed1999

Power loss for multiallelic transmission/disequilibrium test when errors introduced: GAW11 simulated data.

Many researchers are considering the use of transmission/disequilibrium tests (TDT) for trios of genotypes (father, mother, child) as a method for localizing genes associated with complex diseases. We evaluate the effect of random errors (allele changes) in trios on the power to detect linkage. For a marker in the simulated data set, one allele is associated with the fictitious disease in a certain subpopulation. For the data as given (no errors), our power to detect linkage using the multiallelic TDT (TDTmhet) is 68% (critical p-value set at 0.0001). We introduce errors into trios at various rates (1%, 5%, or 10%), remove only trios displaying mendelian inconsistencies, and recalculate power to detect linkage. Our principal finding is that there is power loss to detect linkage with the TDTmhet when errors are introduced. We observe power losses of 8%, 16%, and 48% for error rates of 1%, 5%, and 10%, respectively. To determine the source of the power loss, we perform Monte Carlo simulations. At the 1% and 5% rates, we conclude that power loss is due primarily to loss in sample size. At the 10% rate, we observe substantial power loss due to error introduction in addition to sample size reduction. We also determine, given a particular error rate, the probability that we detect errors if we use only mendelian consistency as a check. We find that the mean detection rates for the data sets with 1%, 5%, or 10% error rates are 58%, 60%, and 62%, respectively. As a result, the apparent error rate appears to be almost half the true error rate. Based on these results, we recommend that researchers maintain error rates below 5% when using the TDTmhet for linkage, use additional methods beyond mendelian consistency checks when searching for errors in their data, and modify sample size calculations when accounting for errors in their genotype data.

Alleles↗

PubMed1999

Multipoint oligogenic analysis of age-at-onset data with applications to Alzheimer disease pedigrees.

It is usually difficult to localize genes that cause diseases with late ages at onset. These diseases frequently exhibit complex modes of inheritance, and only recent generations are available to be genotyped and phenotyped. In this situation, multipoint analysis using traditional exact linkage analysis methods, with many markers and full pedigree information, is a computationally intractable problem. Fortunately, Monte Carlo Markov chain sampling provides a tool to address this issue. By treating age at onset as a right-censored quantitative trait, we expand the methods used by Heath (1997) and illustrate them using an Alzheimer disease (AD) data set. This approach estimates the number, sizes, allele frequencies, and positions of quantitative trait loci (QTLs). In this simultaneous multipoint linkage and segregation analysis method, the QTLs are assumed to be diallelic and to interact additively. In the AD data set, we were able to localize correctly, quickly, and accurately two known genes, despite the existence of substantial genetic heterogeneity, thus demonstrating the great promise of these methods for the dissection of late-onset oligogenic diseases.

Age Factors↗

PubMed1999

Detecting QTLs for uni- and bipolar disorder using a variance component method.

The objective of this study was to use a robust variance component method to analyse unipolar and bipolar disorder in a large Scottish extended family (n = 168) in which linkage between markers and disease has been previously reported on the short arm of chromosome 4. Data consisted of diagnosed clinical uni- or bipolar disorder on 143 individuals, with microsatellite marker information on 109 of these individuals. The incidence of unipolar and bipolar disorder in the family was 17/143, and 11/143, respectively. Eleven linked markers on chromosome 4, spanning a region of approximately 26 cM, were used in the analysis. The statistical analysis was performed in two steps. First, pairwise identify-by-descent (IBD) coefficients for all individuals in the pedigree were calculated at 1 cM intervals, using all marker data simultaneously, with a Monte Carlo Markov Chain algorithm. Second, the variance in the trait of interest was partitioned using residual maximum likelihood (REML). Three components of variance were estimated: (i) a genetic component associated with the average relationship between individuals using the numerator relationship matrix, (ii) a genetic component associated with a chromosome location using the estimated IBD coefficients, and (iii) a residual component. The test statistic (LOD score) was calculated from the maximum likelihood of the full model, fitting all three variance components, and the maximum likelihood value from the reduced model, fitting a polygenic and residual component. The largest LOD scores (maximum LOD = 5.9), were found in a region spanning about 10 cM, when the trait was defined as the occurrence of either uni- or bipolar disorder. The putative QTL explained about 25% of the total variation in the trait.

Bipolar Disorder↗

PubMed1999

True pedigree errors more frequent than apparent errors for single nucleotide polymorphisms.

Single nucleotide polymorphisms (SNPs) are currently being developed for use in disequilibrium analyses. These SNPs consist of two alleles with varying degrees of polymorphism. A natural design for use with SNPs is the 'haplotype relative risk' sampling design in which a father, mother, and child are typed at an SNP locus. Given such a trio of genotypes, we ask: what is the probability that a pedigree error (a change from one allele to the other) at an SNP locus will be detected using only Mendel's laws as a check? We calculate the probability of detecting such errors for a hypothetical SNP locus with varying degrees of polymorphism and for various true error rates. For the sets of allele frequencies considered, we find that the detection rates range between 25 and 30%, the detection rate being lowest when the two alleles have equal frequencies and the highest when one allele has a frequency of 10%. Based on this detection rate, we determine that the true error rate is roughly 3.3-4 times that of the apparent error rate at an SNP locus. The greatest discrepancy between true and apparent error rates occurs when allele frequencies are equal.

Alleles↗

PubMed1999

Heterogeneity for multiple disease loci in linkage analysis.

Many mendelian traits show heterogeneity; that is, the disease phenotype in different families may be caused by genes at different locations. In linkage analysis, this admixture type of heterogeneity (locus heterogeneity) has often been accommodated with one of the HOMOG programs, which thus far have been restricted to at most two disease gene locations. Here, an extension to an arbitrary number of disease locations is described. It has been implemented in a computer program, HOMOGM. This approach is also suitable as an approximation to the situation of complex traits, in which multiple disease genes may occur in the same family.

Algorithms↗

PubMed1999

Genetic background determines the extent of atherosclerosis in ApoE-deficient mice.

Two strains of ApoE-deficient mice were found to have markedly different plasma lipoprotein profiles and susceptibility to atherosclerosis when fed either a low-fat chow or a high-fat Western-type diet. FVB/NJ ApoE-deficient (FVB E0) mice had higher total cholesterol, HDL cholesterol, ApoA1, and ApoA2 levels when compared with C57BL/6J ApoE-deficient (C57 E0) mice. At 16 weeks of age, mean aortic root atherosclerotic lesion area was 7- to 9-fold higher in chow diet-fed C57 E0 mice and 3.5-fold higher in Western diet-fed C57 E0 mice compared with FVB E0 mice fed similar diets. Lesion area in chow diet-fed first-generation mice from a strain intercross was intermediate in size compared with parental values. The distribution of the lesion area in 150 chow diet-fed second-generation progeny spanned the range of the lesion area in both parental strains. There were no correlations between total cholesterol, non-HDL cholesterol, HDL cholesterol, ApoA1, ApoA2, ApoJ, or anti-cardiolipin antibodies and lesion area in the second-generation progeny. Thus, a genomic approach may succeed in identifying the genes responsible for the variation in atherosclerosis susceptibility in these 2 strains of ApoE-deficient mice, which could not be explained by measured plasma parameters.

Animals↗

PubMed1997

MCMC segregation and linkage analysis.

Our objective was to infer the genetic model for the quantitative traits using a variety of methods developed in our group. Only a single data set was analyzed in any one analysis, although some comparison between data sets was made. In addition, the simulated model was not known during the course of the analysis. Basic modeling and segregation analyses for the five quantitative traits was followed by several simple genome scans to indicate areas of interest. A Markov chain Monte Carlo (MCMC) multipoint quantitative trait locus (QTL) mapping approach was then used to estimate the posterior probabilities of linkage of QTL to each chromosome simultaneously with trait model parameters, and to further localize the genes. Comparisons between the nuclear family and pedigree data sets indicated a greater power for QTL detection and mapping with the pedigree data sets. Even with the pedigree data, however, precise localization of the QTL did not appear to be possible using single replicate data sets. Two of the three genes with effects on trait Q1 were detected by the MCMC method.

Chromosome Mapping↗

PubMed1997

Mapping quantitative trait loci for body weight on the X chromosome in mice. II. Analysis of congenic backcrosses.

In a QTL mapping study with an F2 population of mice, we have shown that one or more sex-linked factors account for a large part of the divergence between mouse lines selected for high and low body weight. Here, we describe a study undertaken to map the putative X-linked quantitative trait loci (QTLs) by backcrossing segments of chromosome from the high line onto an inbred line derived from the low line, thereby removing possible contributions from the autosomes and linked segments of the X chromosome. Sublines containing a regional at the proximal end of the X chromosome were found to be associated with large differences in body weight, and to account for almost all the difference between the lines. A Markov chain Monte Carlo based multipoint linkage analysis incorporating the available marker and phenotypic information from the backcross pedigree was used to map the QTL to a region of about 6 cM. There was no evidence for QTLs elsewhere on the chromosome. The estimated QTL effect is approximately 20% of mean body weight in males and females at 10 weeks. From results obtained from this study and the accompanying F2 analysis, we conclude the presence of a single factor for body weight localizing to about position (+/- SE) 26.4 +/- 1.2 cM on the X chromosome, which increases body weight by approximately 18% at 10 weeks. A strategy to positionally clone the QTL is discussed.

Animals↗