Search PubMed⌕ Search

Biomedical subjects

Robert C Elston

Publications and source records attributed to Robert C Elston.

At least 19 recordsLinked to original sources
PubMed2006

Odds ratio based multifactor-dimensionality reduction method for detecting gene-gene interactions.

MOTIVATION: The identification and characterization of genes that increase the susceptibility to common complex multifactorial diseases is a challenging task in genetic association studies. The multifactor dimensionality reduction (MDR) method has been proposed and implemented by Ritchie et al. (2001) to identify the combinations of multilocus genotypes and discrete environmental factors that are associated with a particular disease. However, the original MDR method classifies the combination of multilocus genotypes into high-risk and low-risk groups in an ad hoc manner based on a simple comparison of the ratios of the number of cases and controls. Hence, the MDR approach is prone to false positive and negative errors when the ratio of the number of cases and controls in a combination of genotypes is similar to that in the entire data, or when both the number of cases and controls is small. Hence, we propose the odds ratio based multifactor dimensionality reduction (OR MDR) method that uses the odds ratio as a new quantitative measure of disease risk. RESULTS: While the original MDR method provides a simple binary measure of risk, the OR MDR method provides not only the odds ratio as a quantitative measure of risk but also the ordering of the multilocus combinations from the highest risk to lowest risk groups. Furthermore, the OR MDR method provides a confidence interval for the odds ratio for each multilocus combination, which is extremely informative in judging its importance as a risk factor. The proposed OR MDR method is illustrated using the dataset obtained from the CDC Chronic Fatigue Syndrome Research Group. AVAILABILITY: The program written in R is available.

Fatigue Syndrome, Chronic↗
PubMed2006

Advances in statistical human genetics over the last 25 years.

The past 25 years has seen an explosion in the number of genetic markers that can be measured on DNA samples at an ever decreasing cost. Although basic statistical methods for analysing such data gathered on samples of either independent individuals or family members, one or two markers at a time, were already well developed before this explosion occurred, there has been a corresponding burst in activity to develop multiple marker models to find disease-causing gene variants, capitalizing on the data that have become available, to increase the power of such methods. This has required the concomitant development of faster algorithms to speed up the computation of various likelihoods. For linkage analysis, to obtain the approximate locations for genes of interest, Mendelian segregation models have been extended to be more realistic and statistical models that do not assume specific modes of inheritance have been extended to allow for the analysis of larger pedigree structures. For association analysis, to obtain more precise locations for genes of interest, the recent completion of the first stage of the HapMap project has spurred the development, still underway, of novel experimental designs and analytical methods to combat the curse of dimensionality and the resulting multiple testing problem. Perhaps the greatest current challenge concerns how best to gather and synthesize the many lines of evidence possible in order to discover the genetic determinants underlying complex diseases.

Chromosome Mapping↗
PubMed2006

A genomewide search finds major susceptibility loci for nicotine dependence on chromosome 10 in African Americans.

Epidemiological studies have demonstrated that genetic factors account for at least 50% of the liability for nicotine dependence (ND). Although several linkage studies have been conducted, all samples to date were primarily of European origin. In this study, we conducted a genomewide scan of 1,261 individuals, representing 402 nuclear families, of African American (AA) origin. We examined 385 autosomal microsatellite markers for ND, which was assessed by smoking quantity (SQ), the Heaviness of Smoking Index (HSI), and the Fagerstrom Test for ND (FTND). After performing linkage analyses using various methods implemented in the GENEHUNTER and S.A.G.E. programs, we found a region near marker D10S1432 on chromosome 10q22 that showed a significant linkage to indexed SQ, with a maximum LOD score of 4.17 at 92 cM and suggestive linkage to HSI, SQ, and log-transformed SQ. Additionally, we identified three regions that met the criteria for suggestive linkage to at least one ND measure: on chromosomes 9q31 at marker D9S1825, 11p11 between markers D11S1993 and D11S1344, and 13q13 between markers D13S325 and D13S788. Other locations on chromosomes 15p11, 17q25, and 18q12 exhibited some evidence of linkage for ND (LOD >1.44). The four regions with significant or suggestive linkage were positive for multiple ND measures by multiple statistical methods. Some of these regions have been linked to smoking behavior at nominally significant levels in other studies, which provides independent replication of the regions for ND in different cohorts. In summary, we found significant linkage on chromosome 10q22 and suggestive linkage on chromosomes 9, 11, and 13 for major genetic determinants of ND in an AA sample. Further analysis of these positive regions by fine mapping and/or association analysis is thus warranted. To our knowledge, this study represents the first genomewide linkage scan of ND in an AA sample.

Adolescent↗
PubMed2006

Reduction of sample heterogeneity through use of population substructure: an example from a population of African American families with sarcoidosis.

Sarcoidosis is a granulomatous inflammatory disorder of complex etiology with significant linkage to chromosome 5, and marginal linkage was observed to five other chromosomes in African Americans (AAs) in our previously published genome scan. Because genetic factors underlying complex disease are often population specific, genetic analysis of samples with diverse ancestry (i.e., ethnic confounding) can lead to loss of power. Ethnic confounding is often addressed by stratifying on self-reported race, a controversial and less-than-perfect construct. Here, we propose linkage analysis stratified by genetically determined ancestry as an alternative approach for reducing ethnic confounding. Using data from the 380 microsatellite markers genotyped in the aforementioned genome scan, we clustered AA families into subpopulations on the basis of ancestry similarity. Evidence of two genetically distinct groups was found: subpopulation one (S1) comprised 219 of the 229 families, subpopulation two (S2) consisted of six families (the remaining four families were a mixture). Stratified linkage results suggest that only the S1 families contributed to previously identified linkage signals at 1p22, 3p21-14, 11p15, and 17q21 and that only the S2 families contributed to those found at 5p15-13 and 20q13. Signals on 2p25, 5q11, 5q35, and 9q34 remained significant in both subpopulations, and evidence of a new susceptibility locus at 2q37 was found in S2. These results demonstrate the usefulness of stratifying on genetically determined ancestry, to create genetically homogeneous subsets--more reliable and less controversial than race-stratified subsets--in which to identify genetic factors. Our findings support the presence of sarcoidosis-susceptibility genes in regions identified elsewhere but indicate that these genes are likely to be ancestry specific.

Black or African American↗
PubMed2006

Genetic characterization and fine mapping of susceptibility loci for sarcoidosis in African Americans on chromosome 5.

Sarcoidosis, a systemic granulomatous disease, likely results from both environmental agents and genetic susceptibility. Sarcoidosis is more prevalent in women and, in the United States, African Americans are both more commonly and more severely affected than Caucasians. We report a follow up of the first genome scan for sarcoidosis susceptibility genes in African Americans. Both the genome scan and the present study comprise 229 African American nuclear families ascertained through two or more sibs with sarcoidosis. Regions studied included those which reached a significance in the genome scan of 0.01 (2p25, 5q11, 5q35, 9q34, 11p15 and 20q13), 0.05 (3p25 and 5p15-13) or which replicated previous findings (3p14-11). We performed genotyping with additional markers in the same families used in the genome scan. We examined multi-locus models for epistasis and performed model-based linkage analysis on subsets of the most linked families to characterize the underlying genetic model. The strongest signal was at marker D5S407 (P=0.005) on 5q11.2, using both full and half sibling pairs. Our results support, in an African American population, a sarcoidosis susceptibility gene on chromosome 5q11.2, and a gene protective for sarcoidosis on 5p15.2. These fine mapping results further prioritize the importance of candidate regions on chromosomes 2p25, 3p25, 5q35, 9q34, 11p15 and 20q13 for African Americans. Additionally, our results suggest joint action of the effects of putative genes on chromosome 3p14-11 and 5p15.2. We conclude that multiple susceptibility loci for sarcoidosis exist in African Americans and that some may have interdependent effects on disease pathogenesis.

Black or African American↗
PubMed2006

The affected-/discordant-sib-pair design can guarantee validity of multipoint model-free linkage analysis of incomplete pedigrees when there is marker-marker disequilibrium.

Genomewide linkage studies are tending toward the use of single-nucleotide polymorphisms (SNPs) as the markers of choice. However, linkage disequilibrium (LD) between tightly linked SNPs violates the fundamental assumption of linkage equilibrium (LE) between markers that underlies most multipoint calculation algorithms currently available, and this leads to inflated affected-relative-pair allele-sharing statistics when founders' multilocus genotypes are unknown. In this study, we investigate the impact that the degree of LD, marker allele frequency, and association type have on estimating the probabilities of sharing alleles identical by descent in multipoint calculations and hence on type I error rates of different sib-pair linkage approaches that assume LE. We show that marker-marker LD does not inflate type I error rates of affected sib pair (ASP) statistics in the whole parameter space, and that, in any case, discordant sib pairs (DSPs) can be used to control for marker-marker LD in ASPs. We advocate the ASP/DSP design with appropriate sib-pair statistics that test the difference in allele sharing between ASPs and DSPs.

Chromosome Mapping↗
PubMed2006

Plasma aldosterone is independently associated with the metabolic syndrome.

The aim of this study was to analyze the associations of plasma aldosterone and plasma renin activity with the metabolic syndrome and each of its components. We analyzed data from a family based study in the Seychelles made up of 356 participants (160 men and 196 women) from 69 families of African descent. In multivariable models, plasma aldosterone was associated positively (P < 0.05) with blood pressure in older individuals (interaction with age, P < 0.05) and with waist circumference in men (interaction with sex, P < 0.05) and negatively with high-density lipoprotein cholesterol, in particular in individuals with elevated urinary potassium excretion (interaction with urinary potassium, P < 0.05); plasma renin activity was significantly associated with triglycerides and fasting blood glucose. Plasma aldosterone, but not plasma renin activity, was associated with the metabolic syndrome per se, independently of the association with its separate components. The observation that plasma renin activity was associated with some components of the metabolic syndrome, whereas plasma aldosterone was associated with other components of the metabolic syndrome, suggests different underlying mechanisms. These findings reinforce previous observations suggesting that aldosterone is associated with several cardiovascular risk factors and also suggest that aldosterone might contribute to the increased cardiovascular disease risk in individuals of African descent with the metabolic syndrome.

Africa, Eastern↗
PubMed2006

Extension of the Haseman-Elston regression model to longitudinal data.

We propose an extension to longitudinal data of the Haseman and Elston regression method for linkage analysis. The proposed model is a mixed model having several random effects. As response variable, we investigate the sibship sample mean corrected cross-product (smHE) and the BLUP-mean corrected cross product (pmHE), comparing them with the original squared difference (oHE), the overall mean corrected cross-product (rHE), and the weighted average of the squared difference and the squared mean-corrected sum (wHE). The proposed model allows for the correlation structure of longitudinal data. Also, the model can test for gene x time interaction to discover genetic variation over time. The model was applied in an analysis of the Genetic Analysis Workshop 13 (GAW13) simulated dataset for a quantitative trait simulating systolic blood pressure. Independence models did not preserve the test sizes, while the mixed models with both family and sibpair random effects tended to preserve size well.

Algorithms↗
PubMed2006

Association of specific haplotypes of neurotrophic tyrosine kinase receptor 2 gene (NTRK2) with vulnerability to nicotine dependence in African-Americans and European-Americans.

BACKGROUND: The gene encoding neurotrophic tyrosine kinase receptor 2 (NTRK2) has been localized to a region on chromosome 9q22-q23 that showed a "suggestive" linkage to nicotine dependence (ND) in our previous linkage analyses. However, no association of NTRK2 with ND has been identified. METHODS: Family-based association analyses of 2037 participants (1366 African Americans [AA], 671 European Americans [EA]) representing 602 nuclear families were performed to evaluate association of nine single nucleotide polymorphisms (SNPs) within NTRK2 with ND. RESULTS: Individual SNP-based association analysis indicated that in the EA sample, SNPs rs1659400 and rs1187272 were significantly associated with at least one adjusted ND measure. Haplotype analysis revealed that even after Bonferroni correction, the haplotype T-T-A of rs1659400-rs1187272-rs1122530 had a highly significant positive association, with adjusted ND measures in the EA sample (max Z = 3.78; p = .0001, frequency 59.9%). We further identified a major haplotype, T-G-C-A-A (26%), formed by rs993315-rs736744-rs920776-rs4075274-rs729560, which showed a significant positive association (max Z = 2.97, p = .003) with adjusted ND measures in the AA sample. CONCLUSIONS: These results strongly suggest that NTRK2 is a susceptibility gene for ND. These findings imply that NTRK2 plays a role in the etiology of ND and represents an important biological candidate for further investigation.

Adult↗
PubMed2006

Haplotype-based quantitative trait mapping using a clustering algorithm.

BACKGROUND: With the availability of large-scale, high-density single-nucleotide polymorphism (SNP) markers, substantial effort has been made in identifying disease-causing genes using linkage disequilibrium (LD) mapping by haplotype analysis of unrelated individuals. In addition to complex diseases, many continuously distributed quantitative traits are of primary clinical and health significance. However the development of association mapping methods using unrelated individuals for quantitative traits has received relatively less attention. RESULTS: We recently developed an association mapping method for complex diseases by mining the sharing of haplotype segments (i.e., phased genotype pairs) in affected individuals that are rarely present in normal individuals. In this paper, we extend our previous work to address the problem of quantitative trait mapping from unrelated individuals. The method is non-parametric in nature, and statistical significance can be obtained by a permutation test. It can also be incorporated into the one-way ANCOVA (analysis of covariance) framework so that other factors and covariates can be easily incorporated. The effectiveness of the approach is demonstrated by extensive experimental studies using both simulated and real data sets. The results show that our haplotype-based approach is more robust than two statistical methods based on single markers: a single SNP association test (SSA) and the Mann-Whitney U-test (MWU). The algorithm has been incorporated into our existing software package called HapMiner, which is available from our website at http://www.eecs.case.edu/~jxl175/HapMiner.html. CONCLUSION: For QTL (quantitative trait loci) fine mapping, to identify QTNs (quantitative trait nucleotides) with realistic effects (the contribution of each QTN less than 10% of total variance of the trait), large samples sizes (>or= 500) are needed for all the methods. The overall performance of HapMiner is better than that of the other two methods. Its effectiveness further depends on other factors such as recombination rates and the density of typed SNPs. Haplotype-based methods might provide higher power than methods based on a single SNP when using tag SNPs selected from a small number of samples or some other sources (such as HapMap data). Rank-based statistics usually have much lower power, as shown in our study.

Algorithms↗
PubMed2006

Treatment of uninformative families in mean allele sharing tests for linkage.

Using affected sibling pairs, the mean allele sharing statistic tests for linkage by testing if the mean proportion of alleles that are identical-by-descent (IBD) is equal to a half. The behavior of some versions of the mean allele sharing test statistic depends on whether or not families that are uninformative for their IBD status are included; the SIBPAL version provides less significant values when all families (informative and uninformative) are used than when only informative families are used. Here, we investigate this behavior both analytically and by simulation. Our investigation shows that the main issue is the choice of the variance estimator in the denominator of the statistic. The choice of the denominator is very important and is still not totally resolved. Our mathematical explanation supported by our simulation study might aid in the search for an optimum solution.

Alleles↗
PubMed2006

Prediction of empirical p values from asymptotic p values for conditional logistic affected relative pair linkage analysis.

OBJECTIVE: p Values are inaccurate for model-free linkage analysis using the conditional logistic model if we assume that the LOD score is asymptotically distributed as a simple mixture of chi-square distributions. When analyzing affected relative pairs alone, permuting the allele sharing of relative pairs does not lead to a useful permutation distribution. As an alternative, we have developed regression prediction models that provide more accurate p values. METHODS: Let E(alpha) be the empirical p value, which is the proportion of statistical tests whose LOD score under the null hypothesis exceeds a threshold determined by alpha, the nominal single test significance value. We used simulated data to obtain values of E(alpha) and compared them with alpha. We also developed a regression model, based on sample size, number of covariates in the model, alpha and marker density, to derive predicted p values for both single-point and multipoint analyses. To evaluate our predictions we used another set of simulated data, comparing the Ealpha for these data with those obtained by using the prediction model, referred to as predicted p values (P(alpha)). RESULTS: Under almost all circumstances the values of P(alpha) were closer to the E(alpha) than were the values of alpha. CONCLUSION: The regression models suggested by our analysis provide more accurate alternative p values for model-free linkage analysis when using the conditional logistic model.

Animals↗
PubMed2006

Genome scan for loci predisposing to anxiety disorders using a novel multivariate approach: strong evidence for a chromosome 4 risk locus.

We conducted a 10-centimorgan linkage autosomal genome scan in a set of 19 extended American pedigrees (219 subjects) ascertained through probands with panic disorder. Several anxiety disorders--including social phobia, agoraphobia, and simple phobia--in addition to panic disorder segregate in these families. In previous studies of this sample, linkage analyses were based separately on each of the individual categorical affection diagnoses. Given the substantial comorbidity between anxiety disorders and their probable shared genetic liability, it is clear that this method discards a considerable amount of information. In this article, we propose a new approach that considers panic disorder, simple phobia, social phobia, and agoraphobia as expressions of the same multivariate, putatively genetically influenced trait. We applied the most powerful multipoint Haseman-Elston method, using the grade of membership score generated from a fuzzy clustering of these phenotypes as the dependent variable in Haseman-Elston regression. One region on chromosome 4q31-q34, at marker D4S413 (with multipoint and single-point nominal P values < .00001), showed strong evidence of linkage (genomewide significance at P<.05). The same region is known to be the site of a neuropeptide Y receptor gene, NPY1R (4q31-q32), that was recently connected to anxiolytic-like effects in rats. Several other regions on four chromosomes (4q21.21-22.3, 5q14.2-14.3, 8p23.1, and 14q22.3-23.3) met criteria for suggestive linkage (multipoint nominal P values < .01). Family-by-family analysis did not show any strong evidence of heterogeneity. Our findings support the notion that the major anxiety disorders, including phobias and panic disorder, are complex traits that share at least one susceptibility locus. This method could be applied to other complex traits for which shared genetic-liability factors are thought to be important, such as substance dependencies.

Anxiety↗
PubMed2006

A quantitative linkage score for an association study following a linkage analysis.

BACKGROUND: Currently, a commonly used strategy for mapping complex quantitative traits is to use a genome-wide linkage analysis to narrow suspected genes to regions on a scale of centiMorgans (cM), followed by an association analysis to fine map the genetic variation in regions showing linkage. Two important questions arise in the design and the resulting inference at the association stage of this sequential procedure: (1) how should we design an efficient association study given the information provided by the previous linkage study? and (2) can an association in a linkage region explain, in part, the detected linkage signal? RESULTS: We derive a quantitative linkage score (QLS) based on Haseman-Elston regression (Haseman and Elston 1972) and make use of this score to address both questions. In designing an association study, the selection of a subsample from the linkage study sample can be guided by the linkage information summarized in the QLS. When heterogeneity exists, we show that selection based on the QLS can increase the proportion of sample individuals from the subpopulation affected by a disease allele and therefore greatly improves the power of the association study. For the resulting inference, we frame as a hypothesis test the question of whether a linkage signal in a region can be in part explained by a marker allele. A simple one sided paired t-statistic is defined by comparing the two sets of QLSs obtained with/without modeling a marker association: a significant difference indicates that the marker can at least partly account for the detected linkage. We also show that this statistic can be used to detect a spurious association. CONCLUSION: All our results suggest that a careful examination of QLSs should be helpful for understanding the results of both association and linkage studies.

Alleles↗
PubMed2006

A powerful method of combining measures of association and Hardy-Weinberg disequilibrium for fine-mapping in case-control studies.

We present a new method for fine-mapping a disease susceptibility locus using a case-control design. The new method, termed the 'weighted average (WA) statistic', averages the Cochran-Armitage (CA) trend test statistic and the difference between the Hardy Weinberg disequilibrium test statistics (the HWD trend) for cases and controls. The main features of the WA statistic are that it mitigates against the weaknesses, and maintains the strong points, of both the CA trend test and the HWD trend test. To allow for the extra variance induced by population structure and cryptic relatedness, the WA statistic can be adjusted for variance inflation. Based on the results of a simulation study, when there is no population structure the WA test statistic shows good performance under a variety of genetic disease models. When there is population structure, the adjusted WA statistic maintains the correct probability of type I error. Under all genetic disease models investigated, the adjusted WA statistic has better power than the adjusted CA trend test, the HWD trend test or the product of the adjusted CA trend test and the HWD trend test statistics.

Case-Control Studies↗
PubMed2006

Apolipoprotein E and obstructive sleep apnea: evaluating whether a candidate gene explains a linkage peak.

Evidence from both linkage analyses and association-based analyses has implicated Apoliprotein E (ApoE) as a disease susceptibility locus for obstructive sleep apnea. To further assess the putative role of ApoE in sleep apnea, we performed genotyping, association, and linkage analyses in a cohort assembled to investigate the genetic epidemiology of sleep apnea. Among a subset of the Caucasian families, ten microsatellites, spanning 20 cM, were genotyped in a region near ApoE on chromosome 19 where previous suggestive linkage had been demonstrated using a 9.1-cM genome-wide scan. Haseman-Elston regression analysis, conducted with these fine mapping markers (n=196 sibling pairs, 56 families), showed evidence for linkage to marker AFM210yg9 (p=0.00034), which was increased over that observed with the original scan. ApoE genotyping also was performed on a larger set of data (n=1,211 from 271 families, ages 3-85 years) from the cohort with available DNA. To determine whether the ApoE genotype explains the linkage peak, we included the ApoE genotype as a covariate in regression models. Inclusion of ApoE E2 allele as a covariate reduced the regression coefficient by 18%, suggesting that ApoE does not substantively explain the linkage signal. Finally, we repeated an association-based analysis in the larger sample of 1,211 individuals, and observed a higher prevalence of sleep apnea among individuals with the ApoE E2 allele. Overall, the evidence suggests that there is a disease susceptibility locus for obstructive sleep apnea in the region of ApoE, but ApoE itself is unlikely to be the causative locus.

Adolescent↗
PubMed2006

Distribution and magnitude of type I error of model-based multipoint lod scores: implications for multipoint mod scores.

The multipoint lod score and mod score methods have been advocated for their superior power in detecting linkage. However, little has been done to determine the distribution of multipoint lod scores or to examine the properties of mod scores. In this paper we study the distribution of multipoint lod scores both analytically and by simulation. We also study by simulation the distribution of maximum multipoint lod scores when maximized over different penetrance models. The multipoint lod score is approximately normally distributed with mean and variance that depend on marker informativity, marker density, specified genetic model, number of pedigrees, pedigree structure, and pattern of affection status. When the multipoint lod scores are maximized over a set of assumed penetrances models, an excess of false positive indications of linkage appear under dominant analysis models with low penetrances and under recessive analysis models with high penetrances. Therefore, caution should be taken in interpreting results when employing multipoint lod score and mod score approaches, in particular when inferring the level of linkage significance and the mode of inheritance of a trait.

Chromosome Mapping↗