bluuebunny/crossref_metadata_2025_split huggingface dataset:
Habitat adaptation rather than genetic distance correlates with female preference in fire salamanders (Salamandra salamandra)
Authors: Caspers Barbara A , Junge Claudia , Weitere Markus , Steinfartz Sebastian 
Published: June 2009

AbstractBackgroundAlthough some mechanisms of habitat adaptation of conspecific populations have been recently elucidated, the evolution of female preference has rarely been addressed as a force driving habitat adaptation in natural settings. Habitat adaptation of fire salamanders (Salamandra salamandra), as found in Middle Europe (Germany), can be framed in an explicit phylogeographic framework that allows for the evolution of habitat adaptation between distinct populations to be traced. Typically, females ofS. salamandraonly deposit their larvae in small permanent streams. However, some populations of the western post-glacial recolonization lineage use small temporary ponds as larval habitats. Pond larvae display several habitat-specific adaptations that are absent in stream-adapted larvae. We conducted mate preference tests with females from three distinct German populations in order to determine the influence of habitat adaptation versus neutral genetic distance on female mate choice. Two populations that we tested belong to the western post-glacial recolonization group, but are adapted to either stream or pond habitats. The third population is adapted to streams but represents the eastern recolonization lineage.ResultsDespite large genetic distances with FSTvalues around 0.5, the stream-adapted females preferred males from the same habitat type regardless of genetic distance. Conversely, pond-adapted females did not prefer males from their own population when compared to stream-adapted individuals of either lineage.ConclusionA comparative analysis of our data showed that habitat adaptation rather than neutral genetic distance correlates with female preference in these salamanders, and that habitat-dependent female preference of a specific pond-reproducing population may have been lost during adaptation to the novel environmental conditions of ponds.
PKC∊-Dependent Potentiation of TTX-Resistant NaV1.8 Current by Neurokinin-1 Receptor Activation in Rat Dorsal Root Ganglion Neurons
Authors: Cang Chun-Lei , Zhang Hua , Zhang Yu-Qiu , Zhao Zhi-Qi 
Published: June 2009

Background Substance P (SP), which mainly exists in a subtype of small-diameter dorsal root ganglion (DRG) neurons, is an important signal molecule in pain processing in the spinal cord. Our previous results have proved the expression of SP receptor neurokinin-1 (NK-1) on DRG neurons and its interaction with transient receptor potential vanilloid 1 (TRPV1) receptor. Results In this study we investigated the effect of NK-1 receptor agonist on Nav1.8, a tetrodotoxin (TTX)-resistant sodium channel, in rat small-diameter DRG neurons employing whole-cell patch clamp recordings. NK-1 agonist [Sar9, Met(O2)11]-substance P (Sar-SP) significantly enhanced the Nav1.8 currents in a subgroup of small-diameter DRG neurons under both the normal and inflammatory situation, and the enhancement was blocked by NK-1 antagonist Win51708 and protein kinase C (PKC) inhibitor bisindolylmaleimide (BIM), but not the protein kinase A (PKA) inhibitor H89. In particular, the inhibitor of PKC∊, a PKC isoform, completely blocked this effect. Under current clamp model, Sar-SP reduced the amount of current required to evoke action potentials and increased the firing rate in a subgroup of DRG neurons. Conclusion These data suggest that activation of NK-1 receptor potentiates Nav1.8 sodium current via PKC∊-dependent signaling pathway, probably participating in the generation of inflammatory hyperalgesia.
N-acetylcysteine does not prevent contrast-induced nephropathy after cardiac catheterization in patients with diabetes mellitus and chronic kidney disease: a randomized clinical trial
Authors: Amini Manouchehr , Salarifar Mojtaba , Amirbaigloo Alireza , Masoudkabir Farzad , Esfahani Fatemeh 
Published: June 2009

Abstract

Background
Patients with diabetes mellitus (DM) and chronic kidney disease (CKD) constitute to be a high-risk population for the development of contrast-induced nephropathy (CIN), in which the incidence of CIN is estimated to be as high as 50%. We performed this trial to assess the efficacy of N-acetylcysteine (NAC) in the prevention of this complication.

Methods
In a prospective, double-blind, placebo controlled, randomized clinical trial, we studied 90 patients undergoing elective diagnostic coronary angiography with DM and CKD (serum creatinine ≥ 1.5 mg/dL for men and ≥ 1.4 mg/dL for women). The patients were randomly assigned to receive either oral NAC (600 mg BID, starting 24 h before the procedure) or placebo, in adjunct to hydration. Serum creatinine was measured prior to and 48 h after coronary angiography. The primary end-point was the occurrence of CIN, defined as an increase in serum creatinine ≥ 0.5 mg/dL (44.2 μmol/L) or ≥ 25% above baseline at 48 h after exposure to contrast medium.

Results
Complete data on the outcomes were available on 87 patients, 45 of whom had received NAC. There were no significant differences between the NAC and placebo groups in baseline characteristics, amount of hydration, or type and volume of contrast used, except in gender (male/female, 20/25 and 34/11, respectively; P = 0.005) and the use of statins (62.2% and 37.8%, respectively; P = 0.034). CIN occurred in 5 out of 45 (11.1%) patients in the NAC group and 6 out of 42 (14.3%) patients in the placebo group (P = 0.656).

Conclusion
There was no detectable benefit for the prophylactic administration of oral NAC over an aggressive hydration protocol in patients with DM and CKD.

Trial registration
NCT00808795
Sub-typing of renal cell tumours; contribution of ancillary techniques
Authors: Pradhan Dinesh , Kakkar Nandita , Bal Amanjit , Singh Shrawan Kumar , Joshi Kusum 
Published: June 2009

AbstractBackgroundAdult renal epithelial neoplasms are a heterogeneous group with varying prognosis and outcome requiring sub-classification.MethodsCases of renal cell carcinoma (RCC) in a 10 years period were analyzed with regard to the clinical features and histology. Sections were reviewed by four pathologists and the discordant cases were resolved with the help of Hale's colloidal iron stain, vimentin, CK 7, and vinculin immunostains and electron microscopy.ResultsAmongst the total of 278 cases, clear cell renal cell carcinoma was the commonest tumor with 74.8% cases, followed by papillary RCC 12.2%, chromophobe RCC 7.9%, oncocytoma 1.8%, and one case of collecting duct RCC. Eight cases were of sarcomatoid renal cell carcinoma. In 28/278 cases, diagnoses varied amongst the four pathologists and the discordance was resolved by Hale's colloidal iron stain, CK7 immunostain and electron microscopy. Vimentin and vinculin did not contribute much in differentiating subtypes of renal cell carcinomas. Relative incidence of sub-types of RCCs was compared with other seriesConclusionTo accurately subclassify renal cell carcinomas, simple ancillary techniques would possibly resolve all difficult cases. The relative incidence of sub-types of renal cell carcinoma is relatively consistent the world over. However, in India, RCCs afflict the patients two decades earlier.
Large-scale linkage analysis of 1302 affected relative pairs with rheumatoid arthritis
Authors: Hamshere Marian L , Segurado Ricardo , Moskvina Valentina , Nikolov Ivan , Glaser Beate , Holmans Peter A 
Published: June 2009

Abstract
Rheumatoid arthritis is the most common systematic autoimmune disease and its etiology is believed to have both strong genetic and environmental components. We demonstrate the utility of including genetic and clinical phenotypes as covariates within a linkage analysis framework to search for rheumatoid arthritis susceptibility loci. The raw genotypes of 1302 affected relative pairs were combined from four large family-based samples (North American Rheumatoid Arthritis Consortium, United Kingdom, European Consortium on Rheumatoid Arthritis Families, and Canada). The familiality of the clinical phenotypes was assessed. The affected relative pairs were subjected to autosomal multipoint affected relative-pair linkage analysis. Covariates were included in the linkage analysis to take account of heterogeneity within the sample. Evidence of familiality was observed with age at onset (p << 0.001) and rheumatoid factor (RF) IgM (p << 0.001), but not definite erosions (p = 0.21). Genome-wide significant evidence for linkage was observed on chromosome 6. Genome-wide suggestive evidence for linkage was observed on chromosomes 13 and 20 when conditioning on age at onset, chromosome 15 conditional on gender, and chromosome 19 conditional on RF IgM after allowing for multiple testing of covariates.
A genome-wide ordered-subset linkage analysis for rheumatoid arthritis
Authors: Mandhyan Desh Deep , Kim-Howard Xana , Gaines Matthew , Nath Swapan K 
Published: June 2009

AbstractRheumatoid arthritis (RA) is a chronic, complex autoimmune inflammatory disorder with poorly known etiology. Approximately 1% of the adult population is afflicted with RA. Linkage analysis of RA can be complicated by the presence of phenotypic and genetic heterogeneity. It is shown that the ordered-subset analysis (OSA) technique reduces heterogeneity, increases statistical power for detecting linkage and helps to define the most informative data set for follow-up analysis. We applied OSA to the family data from the North American Rheumatoid Arthritis Consortium study as part of the Genetic Analysis Workshop 15 (GAW15). We have incorporated two continuous covariates, 'age of onset' and 'anti-CCP level' (anti-cyclic citrinullated peptide), into our genome-wide ordered-subset linkage analysis using 809 Illumina SNP markers in 5713 individuals from 606 Caucasian RA families. A statistically significant increase in nonparametric linkage (NPL) scores was observed with covariate 'age of onset' in chromosomes 4 (p= 0.000003) and 9 (p= 0.002). With the covariate 'anti-CCP level', statistically significant increases in NPL scores were observed in chromosomes 2 (p= 0.0001), 18 (p= 0.00007), and 19 (p= 0.0003). Once we identified the linked genomic region, we then attempted to identify the best plausible parametric model at that linked locus. Our results show significant improvement in evidence for linkage and demonstrate that OSA is a useful technique to detect linkage under heterogeneity.
Bayesian hierarchical modeling of means and covariances of gene expression data within families
Authors: Pique-Regi Roger , Morrison John , Thomas Duncan C 
Published: June 2009

Abstract
We describe a hierarchical Bayes model for the influence of constitutional genotypes from a linkage scan on the expression of a large number of genes. The model comprises linear regression models for the means in relation to genotypes and for the covariances between pairs of related individuals in relation to their identity-by-descent estimates. The matrices of regression coefficients for all possible pairs of single-nucleotide polymorphisms (SNPs) by all possible expressed genes are in turn modeled as a mixture of null values and a normal distribution of non-null values, with probabilities and means given by a third-level model of SNP and trait random effects and a spatial regression on the distance between the SNP and the expressed gene. The latter provides a way of testing for cis and trans effects. The method was applied to data on 116 SNPs and 189 genes on chromosome 11, for which Morley et al. (Nature 2004, 430: 743–747) had previously reported linkage. We were able to confirm the association of the expression of HSD17B12 with a SNP in the same region reported by Morley et al., and also detected a SNP that appeared to affect the expression of many genes on this chromosome. The approach appears to be a promising way to address the huge multiple comparisons problem for relating genome-wide genotype × expression data.
Analysis of variation in NF-κB genes and expression levels of NF-κB-regulated molecules
Authors: Liu-Mares Wen , Sun Zhifu , Bamlet William R , Atkinson Elizabeth J , Fridley Brooke L , Slager Susan L , de Andrade Mariza , Goode Ellen L 
Published: June 2009

Abstract
The nuclear factor-kappaB (NF-κB) family of transcription factors regulates the expression of a variety of genes involved in apoptosis and immune response. We examined relationships between genotypes at five NF-κB subunits (NFKB1, NFKB2, REL, RELA, and RELB) and variable expression levels of 15 NF-κB regulated proteins with heritability greater than 0.40: BCL2A1, BIRC2, CD40, CD44, CD80, CFLAR, CR2, FAS, ICAM1, IL15, IRF1, JUNB, MYC, SLC2A5, and VCAM1. SNP genotypes and expression phenotypes from pedigrees of Utah residents with ancestry from northern and western Europe were provided by Genetic Analysis Workshop 15 and supplemented with additional genotype data from the International HapMap Consortium. We conducted association, linkage, and family-based association analyses between each candidate gene and the 15 heritable expression phenotypes. We observed consistent results in association and linkage analyses of the NFKB1 region (encoding p50) and levels of FAS and IRF1 expression. FAS is a cell surface protein that also belongs to the TNF-receptor family; signals through FAS are able to induce apoptosis. IRF1 is a member of the interferon regulatory transcription factor family, which has been shown to regulate apoptosis and tumor-suppression. Analyses in the REL region (encoding c-Rel) revealed linkage and association with CD40 phenotype. CD40 proteins belong to the tumor necrosis factor (TNF)-receptor family, which mediates a broad variety of immune and inflammatory responses. We conclude that variation in the genes encoding p50 and c-Rel may play a role in NF-κB-related transcription of FAS, IRF1, and CD40.
Genome-wide analysis of single-locus and epistasis single-nucleotide polymorphism effects on anti-cyclic citrullinated peptide as a measure of rheumatoid arthritis
Authors: Ma Li , Dvorkin Daniel , Garbe John R , Da Yang 
Published: June 2009

AbstractThe goal of this study was to identify single-locus and epistasis effects of SNP markers on anti-cyclic citrullinated peptide (anti-CCP) that is associated with rheumatoid arthritis, using the North American Rheumatoid Arthritis Consortium data. A square root transformation of the phenotypic values of anti-CCP with sex, smoking status, and a selected subset of 20 single-nucleotide polymorphism (SNP) markers in the model achieved residual normality (p> 0.05). Three single-locus effects of two SNPs were significant (p< 10-4). The epistasis analysis tested five effects of each pair of SNPs, the two-locus interaction, additive × additive, additive × dominance, dominance × additive, and dominance × dominance effects. A total of ten epistasis effects of eight pairs of SNPs on 11 autosomes and the X chromosome had significant epistasis effects (p< 10-7). Three of these epistasis effects reached significance levels ofp< 10-8,p< 10-9, andp< 10-10, respectively. Two potential SNP epistasis networks were identified. The results indicate that the genetic factors underlying anti-CCP may include single-gene action and gene interactions and that the gene-interaction mechanism underlying anti-CCP could be a complex mechanism involving pairwise epistasis effects and multiple SNPs.
Comparison of measures for haplotype similarity
Authors: Marquard Vivien , Beckmann Lars , Bermejo Justo L , Fischer Christine , Chang-Claude Jenny 
Published: June 2009

Abstract
Measuring the association of haplotype similarities with phenotype similarities has been used to develop statistical tests of genetic association. Previously, we applied the general approach of Mantel statistics to correlate genetic and phenotype similarity, where genetic similarity was defined by the number of intervals flanked by markers identical by state for pairs of haplotypes. Here we investigated in the case-control study design the effect on power of the Mantel statistics for five different measures of genetic similarity based on haplotypes: 1) the number of shared intervals, 2) the physical length of the shared intervals, 3) the genetic length of the shared intervals in centimorgans, 4) the genetic length of the shared intervals in linkage disequilibrium units (LDU) and 5) Yu's measure that attaches more weight to the sharing of rare than common alleles. With prior knowledge of the answers of Genetic Analysis Workshop 15 Problem 3, we analyzed the simulated data sets in two genomic regions surrounding the disease loci on chromosomes 6 and 18. For the dense map on chromosome 6, all methods showed a very high power of comparable magnitude. For chromosome 18, we observed a power between 19% and 99% at the pointwise 5% significance level using 1000 cases and 1000 controls for all methods except Yu's measure. While it yielded a much lower power, Yu's measure had 80% power around the disease locus.
Association testing by haplotype-sharing methods applicable to whole-genome analysis
Authors: Nolte Ilja M , de Vries André R , Spijker Geert T , Jansen Ritsert C , Brinza Dumitru , Zelikovsky Alexander , te Meerman Gerard J 
Published: June 2009

Abstract
We propose two new haplotype-sharing methods for identifying disease loci: the haplotype sharing statistic (HSS), which compares length of shared haplotypes between cases and controls, and the CROSS test, which tests whether a case and a control haplotype show less sharing than two random haplotypes. The significance of the HSS is determined using a variance estimate from the theory of U-statistics, whereas the significance of the CROSS test is estimated from a sequential randomization procedure. Both methods are fast and hence practical, even for whole-genome screens with high marker densities. We analyzed data sets of Problems 2 and 3 of Genetic Analysis Workshop 15 and compared HSS and CROSS to conventional association methods. Problem 2 provided a data set of 2300 single-nucleotide polymorphisms (SNPs) in a 10-Mb region of chromosome 18q, which had shown linkage evidence for rheumatoid arthritis. The CROSS test detected a significant association at approximately position 4407 kb. This was supported by single-marker association and HSS. The CROSS test outperformed them both with respect to significance level and signal-to-noise ratio. A 20-kb candidate region could be identified. Problem 3 provided a simulated 10 k SNP data set covering the whole genome. Three known candidate regions for rheumatoid arthritis were detected. Again, the CROSS test gave the most significant results. Furthermore, both the HSS and the CROSS showed better fine-mapping accuracy than straightforward haplotype association. In conclusion, haplotype sharing methods, particularly the CROSS test, show great promise for identifying disease gene loci.
Constructing gene association networks for rheumatoid arthritis using the backward genotype-trait association (BGTA) algorithm
Authors: Ding Yuejing , Cong Lei , Ionita-Laza Iuliana , Lo Shaw-Hwa , Zheng Tian 
Published: June 2009

Abstract

Background
Rheumatoid arthritis (RA, MIM 180300) is a common and complex inflammatory disorder. The North American Rheumatoid Arthritis Consortium (NARAC) data, as part of the Genetic Analysis Workshop 15 data, consists of both genome scan and candidate gene studies on RA patients.

Results
We applied the backward genotype-trait association (BGTA) algorithm to capture marginal and gene × gene interaction effects of multiple susceptibility loci on RA disease status. A two-stage screening approach was used for the genome scan, whereas a comprehensive study of all possible subsets was conducted for the candidate genes. For the genome scan, we constructed an association network among 39 genetic loci that demonstrated strong signals, 19 of which have been reported in the RA literature. For the candidate genes, we found strong signals for PTPN22 and SUMO4. Based on significant association evidence, we built an association network among the loci of PTPN22, PADI4, DLG5, SLC22A4, SUMO4, and CARD15. To control for false positives, we used permutation tests to constrain the family-wise type I error rate to 1%.

Conclusion
Using the BGTA algorithm, we identified genetic loci and candidate genes that were associated with RA susceptibility and association networks among them. For the first time, we report possible interactions between single-nucleotide polymorphisms/genes, which may be useful for biological interpretation.
Two-stage analysis strategy for identifying the IgM quantitative trait locus
Authors: Wang Tao , Lu Qing , Torres-Caban Monica , Elston Robert C 
Published: June 2009

Abstract
Genetic association studies offer an opportunity to find genetic variants underlying complex human diseases. Various tests have been developed to improve their power. However, none of these tests is uniformly best and it is usually unclear at the outset what test is best for a specific dataset. For example, Hotelling's T
2 test is best for normally distributed data, but it can lose considerable power when normality is not met. To achieve satisfactory power in most cases, without compromising the overall significance level, we propose to adopt a two-stage adaptive analysis strategy – several statistics are compared on a portion of the samples at the first stage and the most powerful statistic is then used for the remaining samples. We evaluated this procedure by mapping the quantitative trait locus of IgM with the simulated data in Genetic Analysis Workshop 15 Problem 3. The results show that the gain in power of the two-stage adaptive analysis procedure could be considerable when the initial choice of test statistic is wrong, whereas the loss is relatively small in the case that the optimal test chosen initially is correct.
Statistical corrections of linkage data suggest predominantly cis regulations of gene expression
Authors: Shi Jianxin , Siegmund David O , Levinson Douglas F 
Published: June 2009

AbstractMorley et al. (Nature2004,430:743–747) detected significant linkages to the expression levels of 142 genes (of 3554) at a reported threshold of genome-widep= 0.001 (LOD ≈ 5.3), using 14 three-generation Centre d'Etude du Polymorphisme Humain pedigrees. Most of the linkages (77%) weretrans, i.e., more than 5 Mb from the expressed gene. However, the analysis did not account for the expected anti-conservative effect of the skewed distribution of score- or regression-based statistics in large sibships, or for the possible variance distortion due to correlations among tests. Therefore, we re-analyzed their data, using a robust score statistic for the entire pedigrees and correcting thep-values for skewness. We found that a LOD of 5.3 had a skewness-corrected genome-widep-value of 0.016 instead of 0.001 (a result that we confirmed using simulation), with around 50 expected false positives. We then further corrected for correlation among the (skew-corrected)p-values by using Efron's method for obtaining the empirical null distribution. Setting a threshold of FDR = 10% (Z= 6.4, LOD = 8.9), we detected linkage for the expression levels of 22 genes, 19 of which arecis. Limiting the analysis tocisregions, linkage was detected to the expression levels of 46 genes with 4.6 expected false positives (FDR = 10%).
Genome-wide association tests by using block information in family data
Authors: Tang Rui , Wang Fei , Sha Qiuying , Zhang Shuanglin , Chen Huann-Sheng 
Published: June 2009

AbstractBy applying an association test to analyze the data sets from Genetic Analysis Workshop 15 Problem 3, we compare power using different haplotype-block information. The results from using both of the two different coding schemes show that the test using tight blocks with limited haplotype diversity within each block is more powerful than that using evenly spaced blocks, and the latter is more powerful than that using single-marker blocks. By using carefully chosen haplotype blocks, the power of association tests may be enhanced.