bluuebunny/crossref_metadata_2025 huggingface dataset:
Impact of the diagnosis definition on linkage detection
Authors: Dizier Marie-Hélène , Génin Emmanuelle , Babron Marie Claude , Bourgain Catherine
Published: December 2005

Previous genome scan linkage analyses of the disease Kofendrerd Personality Disorder (KPD) with microsatellites led to detect some regions on chromosomes 1, 3, 5, and 9 that were identical for the three populations AI, KA, and DA but with large differences in significance levels. These differences in results may be explained by the different diagnosis definitions depending on the presence/absence of 12 traits that were used in the 3 populations AI, KA, and DA. Heterogeneity of linkage was thus investigated here according to the absence/presence of each of the 12 traits in the 3 populations. For this purpose, two methods, the triangle test statistic and the predivided sample test were applied to search for genetic heterogeneity. Three regions with a strong heterogeneity of linkage were detected: the region on chromosome 1 according to the presence/absence of the traits a and b, the region on chromosome 3 for the trait b, and the region on chromosome 9 for the traits k and l. These 3 regions were the same as those detected by linkage analyses. No novel region was detected by the heterogeneity tests. Concerning chromosome 1, linkage analyses showed a much stronger evidence of linkage for traits a and b and for a combination of these traits than for KPD. Moreover, there was no indication of linkage to any of the other traits used to define the diagnosis of KPD. A genetic factor located on the chromosome 1 may have been detected here which would be involved specifically in traits a and b or in a combination of these traits.
Analysis of alcohol dependence phenotype in the COGA families using covariates to detect linkage
Authors: Reck Brian H , Mukhopadhyay Nandita , Tsai Hui-Ju , Weeks Daniel E
Published: December 2005

Linkage analysis methods that incorporate etiological heterogeneity of complex diseases are likely to demonstrate greater power than traditional linkage analysis methods. Several such methods use covariates to discriminate between linked and unlinked pedigrees with respect to a certain disease locus. Here we apply several such methods including two mixture models, ordered subset analysis, and a conditional logistic model to genome scan data on the DSM-IV alcohol dependence phenotype on the Collaborative Studies on Genetics of Alcoholism families, and compare the results to traditional nonparametric linkage analysis. In general, there was little agreement among the various covariate-based linkage statistics. Linkage signals with empirical p-values less than 0.001 were detected on chromosomes 3, 4, 7, 10, and 12, with the highest peak occurring at the GABRB1 gene using the ecb21 covariate.
Methods for detecting gene × gene interaction in multiplex extended pedigrees
Authors: Brock Guy N , Maher Brion S , Goldstein Toby H , Cooper Margaret E , Marazita Mary L
Published: December 2005

Complex diseases are multifactorial in nature and can involve multiple loci with gene × gene and gene × environment interactions. Research on methods to uncover the interactions between those genes that confer susceptibility to disease has been extensive, but many of these methods have only been developed for sibling pairs or sibships. In this report, we assess the performance of two methods for finding gene × gene interactions that are applicable to arbitrarily sized pedigrees, one based on correlation in per-family nonparametric linkage scores and another that incorporates candidate loci genotypes as covariates into an affected relative pair linkage analysis. The power and type I error rate of both of these methods was addressed using the simulated Genetic Analysis Workshop 14 data. In general, we found detection of the interacting loci to be a difficult problem, and though we experienced some modest success there is a clear need to continue developing new methods and approaches to the problem.
Multifactor-dimensionality reduction versus family-based association tests in detecting susceptibility loci in discordant sib-pair studies
Authors: Meng Yan , Ma Qianli , Yu Yi , Farrell John , Farrer Lindsay A , Wilcox Marsha A
Published: December 2005

Complex diseases are generally thought to be under the influence of multiple, and possibly interacting, genes. Many association methods have been developed to identify susceptibility genes assuming a single-gene disease model, referred to as single-locus methods. Multilocus methods consider joint effects of multiple genes and environmental factors. One commonly used method for family-based association analysis is implemented in FBAT. The multifactor-dimensionality reduction method (MDR) is a multilocus method, which identifies multiple genetic loci associated with the occurrence of complex disease. Many studies of late onset complex diseases employ a discordant sib pairs design. We compared the FBAT and MDR in their ability to detect susceptibility loci using a discordant sib-pair dataset generated from the simulated data made available to participants in the Genetic Analysis Workshop 14. Using FBAT, we were able to identify the effect of one susceptibility locus. However, the finding was not statistically significant. We were not able to detect any of the interactions using this method. This is probably because the FBAT test is designed to find loci with major effects, not interactions. Using MDR, the best result we obtained identified two interactions. However, neither of these reached a level of statistical significance. This is mainly due to the heterogeneity of the disease trait and noise in the data.
Identifying susceptibility genes by using joint tests of association and linkage and accounting for epistasis
Authors: Millstein Joshua , Siegmund Kimberly D , Conti David V , Gauderman W James
Published: December 2005

Simulated Genetic Analysis Workshop14 data were analyzed by jointly testing linkage and association and by accounting for epistasis using a candidate gene approach. Our group was unblinded to the "answers." The 48 single-nucleotide polymorphisms (SNPs) within the six disease loci were analyzed in addition to five SNPs from each of two non-disease-related loci. Affected sib-parent data was extracted from the first 10 replicates for populations Aipotu, Kaarangar, and Danacaa, and analyzed separately for each replicate. We developed a likelihood for testing association and/or linkage using data from affected sib pairs and their parents. Identical-by-descent (IBD) allele sharing between sibs was explicitly modeled using a conditional logistic regression approach and incorporating a covariate that represents expected IBD allele sharing given the genotypes of the sibs and their parents. Interactions were accounted for by performing likelihood ratio tests in stages determined by the highest order interaction term in the model. In the first stage, main effects were tested independently, and in subsequent stages, multilocus effects were tested conditional on significant marginal effects. A reduction in the number of tests performed was achieved by prescreening gene combinations with a goodness-of-fit chi square statistic that depended on mating-type frequencies. SNP-specific joint effects of linkage and association were identified for loci D1, D2, D3, and D4 in multiple replicates. The strongest effect was for SNP B03T3056, which had a median p-value of 1.98 × 10-34. No two- or three-locus effects were found in more than one replicate.
Searching for epistatic interactions in nuclear families using conditional linkage analysis
Authors: Shah Svati H , Schmidt Michael A , Mei Hao , Scott William K , Hauser Elizabeth R , Schmidt Silke
Published: December 2005

Background

Genomic screens generally employ a single-locus strategy for linkage analysis, but this may have low power in the presence of epistasis. Ordered subsets analysis (OSA) is a method for conditional linkage analysis using continuous covariates.

Methods

We used OSA to evaluate two-locus interactions in the simulated Genetic Analysis Workshop 14 dataset. We used all nuclear families ascertained by Aipotu, Karangar, and Danacaa. Using the single-nucleotide polymorphism map, multipoint affected-sibling-pair (ASP) linkage analysis was performed on all 100 replicates for each chromosome using SIBLINK. OSA was used to examine linkage on each chromosome using LOD scores at each 3-cM location on every other chromosome as covariates. Two methods were used to identify positive results: one searching across the entire covariate chromosome, the other conditioning on location of known disease loci.

Results

Single-locus linkage analysis revealed very high LOD scores for disease loci D1 through D4, with mean LOD scores over 100 replicates ranging from 4.0 to 7.8. Although OSA did not obscure this linkage evidence, it did not detect the simulated interactions between any of the locus pairs. We found inflated type I error rates using the first OSA method, highlighting the need to correct for multiple comparisons. Therefore, using "null chromosome pairs" without simulated disease loci, we calculated a corrected alpha-level.

Conclusion

We were unable to detect two-locus interactions using OSA. This may have been due to lack of incorporation of phenotypic subgroups, or because linkage evidence as summarized by LOD scores performs poorly as an OSA covariate. We found inflated type I error rates, but were able to calculate a corrected alpha-level for future analyses employing this strategy to search for two-locus interactions.
Precision and type I error rate in the presence of genotype errors and missing parental data: a comparison between the original transmission disequilibrium test (TDT) and TDTae statistics
Authors: Barral Sandra , Haynes Chad , Levenstien Mark A , Gordon Derek
Published: December 2005

Background

Two factors impacting robustness of the original transmission disequilibrium test (TDT) are: i) missing parental genotypes and ii) undetected genotype errors. While it is known that independently these factors can inflate false-positive rates for the original TDT, no study has considered either the joint impact of these factors on false-positive rates or the precision score of TDT statistics regarding these factors. By precision score, we mean the absolute difference between disease gene position and the position of markers whose TDT statistic exceeds some threshold.

Methods

We apply our transmission disequilibrium test allowing for errors (TDTae) and the original TDT to phenotype and modified single-nucleotide polymorphism genotype simulation data from Genetic Analysis Workshop. We modify genotype data by randomly introducing genotype errors and removing a percentage of parental genotype data. We compute empirical distributions of each statistic's precision score for a chromosome harboring a simulated disease locus. We also consider inflation in type I error by studying markers on a chromosome harboring no disease locus.

Results

The TDTae shows median precision scores of approximately 13 cM, 2 cM, 0 cM, and 0 cM at the 5%, 1%, 0.1%, and 0.01% significance levels, respectively. By contrast, the original TDT shows median precision scores of approximately 23 cM, 21 cM, 15 cM, and 7 cM at the corresponding significance levels, respectively. For null chromosomes, the original TDT falsely rejects the null hypothesis for 28.8%, 14.8%, 5.4%, and 1.7% at the 5%, 1%, 0.1% and 0.01%, significance levels, respectively, while TDTae maintains the correct false-positive rate.

Conclusion

Because missing parental genotypes and undetected genotype errors are unknown to the investigator, but are expected to be increasingly prevalent in multilocus datasets, we strongly recommend TDTae methods as a standard procedure, particularly where stricter significance levels are required.
Characteristics of replicated single-nucleotide polymorphism genotypes from COGA: Affymetrix and Center for Inherited Disease Research
Authors: Tintle Nathan L , Ahn Kwangmi , Mendell Nancy Role , Gordon Derek , Finch Stephen J
Published: December 2005

Genetic Analysis Workshop 14 provided re-genotyped single-nucleotide polymorphism (SNP) data. Specifically, both Center for Inherited Disease Research (CIDR) and Affymetrix genotyped the same 11,560 SNPs from the Affymetrix GeneChip Mapping 10K Array marker set on the same 184 individuals from the Collaborative Study on the Genetics of Alcoholism database. While the inconsistency rate between CIDR and Affymetrix (two different genotypes for the same subject) was low (0.2%), the non-replication rate (two different genotypes for the same subject or one identified genotype and one missing genotype) was substantial (9.5%). The missing data could be from no-call regions, which is inconsistent with recent recommendations about the use of no-call regions in association tests. In addition, no-call regions would suggest that the actual inconsistency rate is higher than reported. A high inconsistency rate has significant impact on power in related hypothesis tests. In addition, the data are consistent with assumptions made in a recently proposed likelihood ratio test of association for re-genotyped data.
Evaluating outlier loci and their effect on the identification of pedigree errors
Authors: Wang Ke-Sheng , Liu Michelle , Paterson Andrew D
Published: December 2005

Homozygosity outlier loci, which show patterns of variation that are extremely divergent from the rest of the genome, can be evaluated by comparison of the homozygosity under Hardy-Weinberg proportions (the sum of the squares of allele frequencies) with the expected homozygosity under neutrality. Such outlier loci are potentially under selection (balancing selection or directional selection) when genome-wide effects (such as bottleneck and rapid population growth) are excluded. Outlier loci show skewed allele frequencies with respect to neutrality and may therefore affect the identification of pedigree errors. However, choosing neutral markers (excluding outlier loci) for the identification of pedigree errors has been neglected thus far. Our results showed that 4.1%, 5.5%, and 1.5% of the microsatellite markers, Illumina single-nucleotide polymorphisms (SNPs), and Affymetrix SNPs, respectively, on the autosomes appear to be under balancing selection (p≤ 0.01) while 0.8% of the Affymetrix SNPs are consistent with directional selection. On the X-chromosome, 7.7%, 3.2%, and 0.4% of the microsatellite markers, Illumina SNPs, and Affymetrix SNPs, respectively, appear to be under balancing selection. 9.3% of Illumina SNPs and 6.7% of Affymetrix SNPs which have high minor allele frequency (≥40%) appear to be under balancing selection. Pedigree structure errors in 15 of 143 pedigrees were detected using microsatellite markers from the autosomes and/or selected SNPs from chromosomes 1 to 18 of the Illumina and/or selected SNPs from chromosomes 1 to 16 of the Affymetrix. Outlier loci did not make a major difference to the identification of pedigree errors. The Collaborative Study on the Genetics of Alcoholism data has pedigree errors and some of them may be due to sample mix up.
Linkage analysis of alcoholism-related electrophysiological phenotypes: genome scans with microsatellites compared to single-nucleotide polymorphisms
Authors: Bautista Jocelyn F , Quade Shannon RE , Parrado Antonio R , Goddard Katrina AB
Published: December 2005

P300 amplitude is an electrophysiological quantitative trait that is correlated with both alcoholism and smoking status. Using the Collaborative Study on the Genetics of Alcoholism data, we performed model-free linkage analysis to investigate the relationship between alcoholism, P300 amplitude, and habitual smoking. We also analyzed the effect of parent-of-origin on alcoholism, and utilized both microsatellites (MS) markers and single-nucleotide polymorphisms (SNPs). We found significant evidence of linkage for alcoholism to chromosome 10; inclusion of P300 amplitude as a covariate provided additional evidence of linkage to chromosome 12. This same region on chromosome 12 showed some evidence for a parent-of-origin effect. We found evidence of linkage for the P300 phenotype to chromosome 7 in non-smokers, and to chromosome 17 in alcoholics. The effects of alcoholism and habitual smoking on P300 amplitude appear to have separate genetic determinants. Overall, there were few differences between MS and SNP genome scans. The use of covariates and parent-of-origin effects allowed detection of linkage not seen otherwise.
X chromosome effects and their interactions with mitochondrial effects
Authors: Kent Jack W , Lease Loren R , Mahaney Michael C , Dyer Thomas D , Almasy Laura , Blangero John
Published: December 2005

We report a simple and rapid method for detecting additive genetic variance due to X-linked loci in the absence of marker data for this chromosome. We examined the interaction of this method with an established method for detecting mitochondrial linkage (another source of sex-asymmetric genetic covariance). When applied to data from the Collaborative Study on the Genetics of Alcoholism, this method found evidence of X-chromosomal linkage for one continuous trait (ntth1) and one discrete trait (SPENT). Evidence of mitochondrial contribution was found for one discrete trait (CRAVING) and three continuous traits (ln(CIGPKYR), ecb21, and tth1). Results for ntth1 suggest that methods that do not also allow for male-female heterogeneity in environmental variance may be overly conservative in detection of X-chromosomal effects.
Recursive partitioning models for linkage in COGA data
Authors: Xu Wei , Taylor Chelsea , Veenstra Justin , Bull Shelley B , Corey Mary , Greenwood Celia MT
Published: January 2006

We have developed a recursive-partitioning (RP) algorithm for identifying phenotype and covariate groupings that interact with the evidence for linkage. This data-mining approach for detecting gene × environment interactions uses genotype and covariate data on affected relative pairs to find evidence for linkage heterogeneity across covariate-defined subgroups. We adapted a likelihood-ratio based test of linkage parameterized with relative risks to a recursive partitioning framework, including a cross-validation based deviance measurement for choosing optimal tree size and a bootstrap sampling procedure for choosing robust tree structure.

ALDX2 category 5 individuals were considered affected, categories 1 and 3 unaffected, and all others unknown. We sampled non-overlapping affected relative pairs from each family; therefore, we used 144 affected pairs in the RP model. Twenty pair-level covariates were defined from smoking status, maximum drinks, ethnicity, sex, and age at onset. Using the all-pairs score in GENEHUNTER, the nonparametric linkage tests showed no regions with suggestive linkage evidence. However, using the RP model, several suggestive regions were found on chromosomes 2, 4, 6, 14, and 20, with detection of associated covariates such as sex and age at onset.
Genome-wide linkage and association mapping of disease genes with the GAW14 simulated datasets
Authors: Carter Kim W , McCaskie Pamela A , Palmer Lyle J
Published: January 2006

We combined the results of whole-genome linkage and association analyses to determine which markers were most strongly associated with Kofendrerd Personality Disorder. Using replicate 1 from the Genetic Analysis Workshop 14 Aipotu, Karangar, Danacaa, and New York City simulated populations, we determined that several markers showed significant linkage and association with disease status. We used both SNP and microsatellite markers to determine patterns and chromosomal regions of markers. Three consistently associated markers were C01R0050, C03R0280, and C10R0882. Using generalized linear mixed models, we modelled the effect of the three predefined phenotypic categories on disease status and concluded that the phenotypes defining the "anxiety-related" category best predicted the outcome.
Including endophenotypes as covariates in variance component heritability and linkage analysis
Authors: Bailey Julia N
Published: January 2006

The purpose of these analyses was to determine if incorporating or adjusting for covariates in genetic analyses helped or hindered in genetic analyses, specifically heritability and linkage analyses. To study this question, two types of covariate models were used in the simulated Genetic Analysis Workshop 14 dataset in which the true gene locations are known. All four populations of one replicate were combined for the analyses. The first model included typical covariates of sex and cohort (population) and the second included the typical covariates and also those related endophenotypes that are thought to be associated with the trait (phenotypes A, B, C, D, E, F, G, H, I, J, K, and L). A final best fit model produced in the heritability analyses was used for linkage. Linkage for disease genes D1, D3, and D4 were localized using models with and without the covariates. The use of inclusion of covariates did not appear to have any consistent advantage or disadvantage for the different phenotypes in regards to gene localization or false positive rate.
Comparison of type I error for multiple test corrections in large single-nucleotide polymorphism studies using principal components versus haplotype blocking algorithms
Authors: Nicodemus Kristin K , Liu Wenlei , Chase Gary A , Tsai Ya-Yu , Fallin M Daniele
Published: December 2005

Although permutation testing has been the gold standard for assessing significance levels in studies using multiple markers, it is time-consuming. A Bonferroni correction to the nominal p-value that uses the underlying pair-wise linkage disequilibrium (LD) structure among the markers to determine the number of effectively independent tests has recently been proposed. We propose using the number of independent LD blocks plus the number of independent single-nucleotide polymorphisms for correction. Using the Collaborative Study on the Genetics of Alcoholism LD data for chromosome 21, we simulated 1,000 replicates of parent-child trio data under the null hypothesis with two levels of LD: moderate and high. Assuming haplotype blocks were independent, we calculated the number of independent statistical tests using 3 haplotype blocking algorithms. We then compared the type I error rates using a principal components-based method, the three blocking methods, a traditional Bonferroni correction, and the unadjusted p-values obtained from FBAT. Under high LD conditions, the PC method and one of the blocking methods were slightly conservative, whereas the 2 other blocking methods exceeded the target type I error rate. Under conditions of moderate LD, we show that the blocking algorithm corrections are closest to the desired type I error, although still slightly conservative, with the principal components-based method being almost as conservative as the traditional Bonferroni correction.
Haplotype sharing correlation of alcohol dependence on chromosomes 1–6 in 93 nuclear families
Authors: Qian Dajun
Published: December 2005

Haplotype data contain signatures of ancestral alleles and increased information for mapping genes associated with complex traits. The motivation of this paper is to test the feasibility of a recently developed haplotype reconstruction algorithm and to perform haplotype-sharing correlation (HSC) analysis in nuclear families using data provided by the Genetic Analysis Workshop 14 and the Collaborative Study of the Genetics of Alcoholism. As an exemplary analysis, haplotype data on chromosomes 1–6 were reconstructed from genotype data in 93 nuclear families by minimizing both the recombinants in within-family haplotypes and the tree distance in between-family haplotypes. HSC analysis was performed using the best set of reconstructed haplotypes, and chromosome-wide significance was evaluated using a permutation procedure. Three markers were found to have significant haplotype associations with DSM-IV alcohol dependence that exceeded the 0.05 level of chromosome-wide significance: marker rs895941 at 36.7 cM on chromosome 3 (p = 0.03), marker rs1631833 at 109.1 cM on chromosome 4 (p = 0.008), and marker rs953887 at 74.2 cM on chromosome 6 (p = 0.02). These results indicated the usefulness of HSC analysis and provided further evidence on chromosome regions associated with alcohol dependence.
Genome-wide linkage analysis for alcohol dependence: a comparison between single-nucleotide polymorphism and microsatellite marker assays
Authors: Ma Qianli , Yu Yi , Meng Yan , Farrell John , Farrer Lindsay A , Wilcox Marsha A
Published: December 2005

Both theoretical and applied studies have proven that the utility of single nucleotide polymorphism (SNP) markers in linkage analysis is more powerful and cost-effective than current microsatellite marker assays. Here we performed a whole-genome scan on 115 White, non-Hispanic families segregating for alcohol dependence, using one 10.3-cM microsatellite marker set and two SNP data sets (0.33-cM, 0.78-cM spacing). Two definitions of alcohol dependence (ALDX1 and ALDX2) were used. Our multipoint nonparametric linkage analysis found alcoholism was nominal linked to 12 genomic regions. The linkage peaks obtained by using the microsatellite marker set and the two SNP sets had a high degree of correspondence in general, but the microsatellite marker set was insufficient to detect some nominal linkage peaks. The presence of linkage disequilibrium between markers did not significantly affect the results. Across the entire genome, SNP datasets had a much higher average linkage information content (0.33 cM: 0.93, 0.78 cM: 0.91) than did microsatellite marker set (0.57). The linkage peaks obtained through two SNP datasets were very similar with some minor differences. We conclude that genome-wide linkage analysis by using approximately 5,000 SNP markers evenly distributed across the human genome is sufficient and might be more powerful than current 10-cM microsatellite marker assays.
Accuracy of haplotype estimation in a region of low linkage disequilibrium
Authors: Avery Christy L , Martin Lisa J , Williams Jeff T , North Kari E
Published: December 2005

We compared the accuracy of haplotype inferences at a 6 Mb region on chromosome 7 where significant linkage between a brain oscillation phenotype and a cholinergic muscarinic receptor gene was previously reported. Individual haplotype assignments and haplotype frequencies were estimated using 5, 10, and 14 consecutive Illumina single-nucleotide polymorphisms (SNPs) within the 1-LOD unit support interval of the chromosome 7 linkage peak. Initially, haplotypes were constructed incorporating phase information provided by relatives using the pedigree analysis package MERLIN. Population-based haplotypes were inferred using the haplotype estimation software HAPLO.STATS and PHASE, using unrelated individuals.

The 14 SNPs within this region exhibited markedly low linkage disequilibrium, and the average D' estimate between SNPs was 0.18 (range: 0.01–0.97). In comparison to the family-based haplotypes calculated in MERLIN, the computational inferences of individual haplotype assignments were most accurate when considering 5 consecutive SNPs, but decayed dramatically when considering 10 or 14 SNPs in both PHASE and HAPLO.STATS. When comparing the two haplotype inference methods, both PHASE and HAPLO.STATS performed poorly. These analyses underscore the difficulties of haplotype estimation in the presence of low linkage disequilibrium and stress the importance of careful consideration of confidence measures when using estimated haplotype frequencies and individual assignments in biomedical research.
An exploration of sex-specific linkage disequilibrium on chromosome X in Caucasians from the COGA study
Authors: Cox Miranda E , Campbell Joel K , Langefeld Carl D
Published: December 2005

This paper explores the decay of linkage disequilibrium (LD) on the autosomes and chromosome X. The extent of marker-marker LD is important for both linkage and association studies. The analysis of the Caucasian sample from the Collaborative Study on the Genetics of Alcoholism study revealed the expected negative relationship between the magnitude of the marker-marker LD and distance (cM), with the male and female subgroups exhibiting similar patterns of LD. The observed extent of LD in females was less across the pseudoautosomal markers relative to the heterosomal region of chromosome X. Marked differences in LD patterns were also observed between chromosomes X and the 22 autosomes in both males and females.
Bias of allele-sharing linkage statistics in the presence of intermarker linkage disequilibrium
Authors: Goode Ellen L , Badzioch Michael D , Jarvik Gail P
Published: December 2005

Current genome-wide linkage-mapping single-nucleotide polymorphism (SNP) panels with densities of 0.3 cM are likely to have increased intermarker linkage disequilibrium (LD) compared to 5-cM microsatellite panels. The resulting difference in haplotype frequencies versus that predicted may affect multipoint linkage analysis with ungenotyped founders; a common haplotype may be assumed to be rare, leading to inflation of identical-by-descent (IBD) allele-sharing estimates and evidence for linkage. Using data simulated for the Genetic Analysis Workshop 14, we assessed bias in allele-sharing measures and nonparametric linkage (NPLall) and Kong and Cox LOD (KC-LOD) scores in a targeted analysis of regions with and without LD and with and without genes. Using over 100 replicates, we found that if founders were not genotyped, multipoint IBD estimates and δ parameters were modestly inflated and NPLall and KC-LOD scores were biased upwards in the region with LD and no gene; rather than centering on the null, the mean NPLall and KC-LOD scores were 0.51 ± 0.91 and 0.19 ± 0.38, respectively. Reduction of LD by dropping markers reduced this upward bias. These trends were not seen in the non-LD region with no gene. In regions with genes (with and without LD), a slight loss in power with dropping markers was suggested. These results indicate that LD should be considered in dense scans; removal of markers in LD may reduce false-positive results although information may also be lost. Methods to address LD in a high-throughput manner are needed for efficient, robust genomic scans with dense SNPs.
The efficacy of short tandem repeat polymorphisms versus single-nucleotide polymorphisms for resolving population structure
Authors: Kauwe John SK , Bertelsen Sarah , Bierut Laura Jean , Dunn Gerald , Hinrichs Anthony L , Jin Carol H , Suarez Brian K
Published: December 2005

Accurately resolving population structure in a sample is important for both linkage and association studies. In this study we investigated the power of single-nucleotide polymorphisms (SNPs) in detecting population structure in a sample of 286 unrelated individuals. We varied the number of SNPs to determine how many are required to approach the degree of resolution obtained with the Collaborative Study on the Genetics of Alcoholism (COGA) short tandem repeat polymorphisms (STRPs). In addition, we selected SNPs with varying minor allele frequencies (MAFs) to determine whether low or high frequency SNPs are more efficient in resolving population structure. We conclude that a set of at least 100 evenly spaced SNPs with MAFs of 40–50% is required to resolve population structure in this dataset. If SNPs with lower MAFs are used, then more than 250 SNPs may be required to obtain reliable results.
Action potential repolarization enabled by Ca++ channel deactivation in PSpice simulation of smooth muscle propagation
Authors: Ramasamy Lakshminarayanan , Sperelakis Nicholas
Published: December 2005

Background

Previously, only the rising phase of the action potential (AP) in cardiac muscle and smooth muscle could be simulated due to the instability of PSpice upon insertion of a second black box (BB) into the K+ leg of the basic membrane unit. This restriction was acceptable because only the transmission of excitation from one cell to the next was investigated.

Methods

In the current work, the repolarization of the AP was accomplished by inserting a second BB into the Ca++ leg of the basic membrane unit. Repolarization of the AP was produced, not through an activation of the K+ channel conductance, but rather through a mimicking of the deactivation of the Ca++ channel conductance. Propagation of complete APs was studied in a chain (strand) of 10 smooth muscle cells, in which various numbers of gap-junction (gj) channels (assumed to be 100 pS each) were inserted across the cell junctions.

Results

The shunt resistance across the junctions produced by the gj-channels (Rgj) was varied from 100,000 MΩ (0 gj-channels) to 10,000 MΩ (1 gj-channel), to 1,000 MΩ (10 channels), to 100 MΩ (100 channels), to 10 MΩ (1000 channels), and to 1.0 MΩ (10,000 channels). Velocity of propagation (θ, in cm/sec) was calculated from the measured total propagation time (TPT, the time difference between when the AP rising phase of the first cell and the last cell crossed -20 mV), assuming a constant cell length of 200 μm. When there were no gj-channels, or only one, the transmission of excitation between cells was produced by the electric field (EF), i.e., the negative junctional cleft potential, that is generated in the narrow junctional clefts (e.g., 100 A) when the prejunctional membrane fires an AP (a fraction of a millisecond before the adjacent surface membrane). There were significant end-effects at the termination of the strand, such that the last cell (cell #10) failed to fire, or fired after a prolonged delay. This end-effect was abolished when the strand termination resistance (Rbt) was increased from 1.0 KΩ to 600 MΩ. When there were 1000 or 10,000 gj-channels, the transmission of excitation was produced by local-circuit current flow from one cell to the next through the gj-channels.

Discussion

In summary, it is now possible to simulate complete APs in smooth muscle cells that could propagate along a single chain of 10 cells, even when there were no gj-channels between the cells.
Surgical resection for gastrointestinal stromal tumors (GIST): experience on 25 patients
Authors: Boni Luigi , Benevento Angelo , Dionigi Gianlorenzo , Rovera Francesca , Dionigi Renzo
Published: December 2005

Background

Gastrointestinal stromal tumors (GIST) are infrequent and diagnosis and prognosis could be troublesome. We present short and long term results of surgical resection for GIST at the Department of Surgery, University of Insubria, during a period of 17 years.

Materials and methods

All patients' data, tumor characteristics, surgical procedure and survival data were analyzed retrospectively. Tumors were divided in risk classes using the classification proposed by Fletcher, based on tumor size and number of mitosis.

Results

Between 1987 and 2004, 25 patients underwent surgical resection for GIST. Stomach was the most common site of localization. Complete resection was achieved in 88% cases, while in 12% radical resection was not possible. The mean tumor size was 9.2 cm (1.2 – 30 cm): <5 cm diameter in 14/25 cases (56%), 5–10 cm in 5/25 (20%) and >10 cm in 6/25 (24%). Mitotic count was <10/50 HPF in 68% (17/25) and >10/50 in 32% (8/25). Using Fletcher's classification, tumors were divided in very low (11/25, 44%), low (4/25, 16%), intermediate (6/25, 24%) and high-risk (4/25, 16%) groups. The 5-year overall survival was 65% and 34% respectively with a statistically significant difference between tumors <5 cm and >10 cm in diameter and between complete and incomplete resection. High-risk tumors had a significantly shorter survival than low or very low risk.

Conclusion

Our experience confirms that GIST's are uncommon and aggressive cancers. The prognosis is strictly related to tumor size and number of mitosis. Although significant advances on new chemotherapeutic regimes have been made, to date, only radical surgery offers the chance of long-term survival.
17beta-estradiol suppresses TLR3-induced cytokine and chemokine production in endometrial epithelial cells
Authors: Lesmeister Margaret J , Jorgenson Rebecca L , Young Steven L , Misfeldt Michael L
Published: December 2005

Background

The human endometrium is an important site for contact between the host and pathogens ascending the reproductive tract, and thus plays an important role in female reproductive tract immunity. Previous work in our laboratory has suggested that Toll-like receptors (TLRs) are involved in endometrial epithelial recognition of pathogens and that ligation of endometrial TLRs results in the production of cytokines and chemokines important for both immune and reproductive functions of the endometrium. We have also demonstrated cyclic regulation of TLR3 mRNA and protein expression in human endometrium, suggesting that steroid hormones might play a role in the expression and function of TLR3. In this study, the effects of 17beta-estradiol (E2) and progesterone (P) on TLR3 expression and function in endometrial cell lines were investigated.

Methods

Endometrial epithelial cell lines were cultured and examined for the presence of TLR3 and hormone receptors by endpoint RT-PCR. For hormonal studies, cells were pre-treated with ethanol vehicle, 10^(-8) M E2, and/or 10^(-7) M P. For antagonist assays, cells were treated with the ER antagonist, ICI 182, 780, or the PR antagonist, RU486, for two hours prior to treatment with hormones. Following hormone or hormone/antagonist pre-treatment, cells were stimulated with vehicle, the synthetic TLR3 ligand, polyinosinic-polycytidylic acid (Poly I:C), a negative dsDNA control, or a positive control. Cytokine and chemokine production post-stimulation was measured by ELISA. The effects of E2 and P on TLR3 mRNA and protein expression were measured using Real Time RT-PCR and FACS analysis, respectively.

Results

Stimulation of TLR3-expressing cells with the synthetic TLR3 ligand, Poly I:C, resulted in the production of cytokines and chemokines important for endometrial function and regulation. Suppression of Poly I:C-induced cytokine and chemokine production by cells treated with 10^(-8) M E2, but not cells treated with 10^(-7) M P, was observed in endometrial epithelial cell lines expressing TLR3 and estrogen receptor alpha (ERalpha). The effects of E2 were not observed on cells which did not express ERalpha or in cells pre-treated with the ER antagonist, ICI 182, 780. Treatment with E2 did not affect TLR3 mRNA or protein expression. However, treatment with E2 did suppress cytokine and chemokine production resulting from TLR3 stimulation with Poly I:C, suggesting that E2 modulates TLR3 function.

Conclusion

The data presented in this study are the first indication that E2 can markedly alter the innate immune response to dsRNA, providing a previously unreported process by which E2 can alter immune responses.
Harnessing information and communication technologies to leverage scarce resources for cancer education, research and practice in developing countries
Authors: Andela Valentine B
Published: January 2006

In developing countries, low levels of awareness, cost and organizational constraints on access to specialized care contribute to inadequate patient help-seeking behavior. As much as 95% of cancer patients in developing countries are diagnosed at late to end stage disease. Consequently, treatment outcome is dismally poor and a vicious cycle sets in, with public mystification of cancer and the admonishment of cancer medicine as a futile effort, all, to the further detriment of patient help-seeking behavior and treatment engagement. The situation spirals down, when the practice of cancer medicine is not gratifying to the medical practitioner and does not appeal as a medical specialty to those in training. The future of cancer medicine in developing countries thus hinges on the demystification of cancer through positive information, coupled to an effective organization that allows for the optimal use of available resources, facilitates access to specialized care and promotes the flow of knowledge and technology amongst various stakeholders. This paper strives to make a cogent argument and highlight the capital importance of information and communication technologies in organizing and leveraging scarce resources for cancer education, research and practice in developing countries.
Immature monocyte derived dendritic cells gene expression profile in response to Virus-Like Particles stimulation
Authors: Aricò Eleonora , Wang Ena , Tornesello Maria Lina , Tagliamonte Maria , Lewis George K , Marincola Francesco M , Buonaguro Franco M , Buonaguro Luigi
Published: December 2005

We have recently developed a candidate HIV-1 vaccine model based on HIV-1 Pr55gag Virus-Like Particles (HIV-VLPs), produced in a baculovirus expression system and presenting a gp120 molecule from an Ugandan HIV-1 isolate of the clade A (HIV-VLPAs).

The HIV-VLPAs induce in Balb/c mice systemic and mucosal neutralizing Antibodies as well as cytotoxic T lymphocytes, by intra-peritoneal as well as intra-nasal administration. Moreover, we have recently shown that the baculovirus-expressed HIV-VLPs induce maturation and activation of monocyte-derived dendritic cells (MDDCs) which, in turn, produce Th1- and Th2-specific cytokines and stimulatein vitroa primary and secondary response in autologous CD4+ T cells.

In the present manuscript, the effects of the baculovirus-expressed HIV-VLPAs on the genomic transcriptional profile of MDDCs obtained from normal healthy donors have been evaluated. The HIV-VLPAstimulation, compared to both PBS and LPS treatment, modulate the expression of genes involved in the morphological and functional changes characterizing the MDDCs activation and maturation.

The results of gene profiling analysis here presented are highly informative on the global pattern of gene expression alteration underlying the activation of MDDCs by HIV-VLPAs at the early stages of the immune response and may be extremely helpful for the identification of exclusive activation markers.
Attenuation of murine antigen-induced arthritis by treatment with a decoy oligodeoxynucleotide inhibiting signal transducer and activator of transcription-1 (STAT-1)
Authors: Hückel Marion , Schurigt Uta , Wagner Andreas H , Stöckigt Renate , Petrow Peter K , Thoss Klaus , Gajda Mieczyslaw , Henzgen Steffen , Hecker Markus , Bräuer Rolf
Published: December 2005

The transcription factor STAT-1 (signal transducer and activator of transcription-1) plays a pivotal role in the expression of inflammatory gene products involved in the pathogenesis of arthritis such as various cytokines and the CD40/CD40 ligand (CD40/CD40L) receptor-ligand dyad. The therapeutic efficacy of a synthetic decoy oligodeoxynucleotide (ODN) binding and neutralizing STAT-1 was tested in murine antigen-induced arthritis (AIA) as a model for human rheumatoid arthritis (RA). The STAT-1 decoy ODN was injected intra-articularly in methylated bovine serum albumin (mBSA)-immunized mice 4 h before arthritis induction. Arthritis was evaluated by joint swelling measurement and histological evaluation and compared to treatment with mutant control ODN. Serum levels of pro-inflammatory cytokines, mBSA-specific antibodies and auto-antibodies against matrix constituents were assessed by enzyme-linked immunosorbent assay (ELISA). The transcription factor neutralizing efficacy of the STAT-1 decoy ODN was verified in vitro in cultured synoviocytes and macrophages. Single administration of STAT-1 decoy ODN dose-dependently suppressed joint swelling and histological signs of acute and chronic arthritis. Delayed-type hypersensitivity (DTH) reaction, serum levels of interleukin-6 (IL-6) and anti-proteoglycan IgG titres were significantly reduced in STAT-1 decoy ODN-treated mice, whereas mBSA, collagen type I and type II specific immunoglobulins were not significantly affected. Intra-articular administration of an anti-CD40L (anti-CD154) antibody was similarly effective. Electrophoretic mobility shift analysis (EMSA) of nuclear extracts from synoviocytes incubated with the STAT-1 decoy ODN in vitro revealed an inhibitory effect on STAT-1. Furthermore, the STAT-1 decoy ODN inhibited the expression of CD40 mRNA in stimulated macrophages. The beneficial effects of the STAT-1 decoy ODN in experimental arthritis presumably mediated in part by affecting CD40 signalling in macrophages may provide the basis for a novel treatment of human RA.
Long term evaluation of disease progression through the quantitative magnetic resonance imaging of symptomatic knee osteoarthritis patients: correlation with clinical symptoms and radiographic changes
Authors: Raynauld Jean-Pierre , Martel-Pelletier Johanne , Berthiaume Marie-Josée , Beaudoin Gilles , Choquette Denis , Haraoui Boulos , Tannenbaum Hyman , Meyer Joan M , Beary John F , Cline Gary A , Pelletier Jean-Pierre
Published: December 2005

The objective of this study was to further explore the cartilage volume changes in knee osteoarthritis (OA) over time using quantitative magnetic resonance imaging (qMRI). These were correlated with demographic, clinical, and radiological data to better identify the disease risk features. We selected 107 patients from a large trial (n = 1,232) evaluating the effect of a bisphosphonate on OA knees. The MRI acquisitions of the knee were done at baseline, 12, and 24 months. Cartilage volume from the global, medial, and lateral compartments was quantified. The changes were contrasted with clinical data and other MRI anatomical features. Knee OA cartilage volume losses were statistically significant compared to baseline values: -3.7 ± 3.0% for global cartilage and -5.5 ± 4.3% for the medial compartment at 12 months, and -5.7 ± 4.4% and -8.3 ± 6.5%, respectively, at 24 months. Three different populations were identified according to cartilage volume loss: fast (n = 11; -13.2%), intermediate (n = 48; -7.2%), and slow (n = 48; -2.3%) progressors. The predictors of fast progressors were the presence of severe meniscal extrusion (p = 0.001), severe medial tear (p = 0.005), medial and/or lateral bone edema (p = 0.03), high body mass index (p < 0.05, fast versus slow), weight (p < 0.05, fast versus slow) and age (p < 0.05 fast versus slow). The loss of cartilage volume was also slightly associated with less knee pain. No association was found with other Western Ontario McMaster Osteoarthritis Index (WOMAC) scores, joint space width, or urine biomarker levels. Meniscal damage and bone edema are closely associated with more cartilage volume loss. These data confirm the significant advantage of qMRI for reliably measuring knee structural changes at as early as 12 months, and for identifying risk factors associated with OA progression.