Improving the sensitivity of the sequence profile method.

The sequence profile method (Gribskov M, McLachlan AD, Eisenberg D, 1987, Proc Natl Acad Sci USA 84:4355-4358) is a powerful tool to detect distant relationships between amino acid sequences. A profile is a table of position-specific scores and gap penalties, providing a generalized description of a protein motif, which can be used for sequence alignments and database searches instead of an individual sequence. A sequence profile is derived from a multiple sequence alignment. We have found 2 ways to improve the sensitivity of sequence profiles: (1) Sequence weights: Usage of individual weights for each sequence avoids bias toward closely related sequences. These weights are automatically assigned based on the distance of the sequences using a published procedure (Sibbald PR, Argos P, 1990, J Mol Biol 216:813-818). (2) Amino acid substitution table: In addition to the alignment, the construction of a profile also needs an amino acid substitution table. We have found that in some cases a new table, the BLOSUM45 table (Henikoff S, Henikoff JG, 1992, Proc Natl Acad Sci USA 89:10915-10919), is more sensitive than the original Dayhoff table or the modified Dayhoff table used in the current implementation. Profiles derived by the improved method are more sensitive and selective in a number of cases where previous methods have failed to completely separate true members from false positives.

Test of four colon cancer risk-scores in formalin fixed paraffin embedded microarray gene expression data.

BACKGROUND: Prognosis prediction for resected primary colon cancer is based on the T-stage Node Metastasis (TNM) staging system. We investigated if four well-documented gene expression risk scores can improve patient stratification. METHODS: Microarray-based versions of risk-scores were applied to a large independent cohort of 688 stage II/III tumors from the PETACC-3 trial. Prognostic value for relapse-free survival (RFS), survival after relapse (SAR), and overall survival (OS) was assessed by regression analysis. To assess improvement over a reference, prognostic model was assessed with the area under curve (AUC) of receiver operating characteristic (ROC) curves. All statistical tests were two-sided, except the AUC increase. RESULTS: All four risk scores (RSs) showed a statistically significant association (single-test, P < .0167) with OS or RFS in univariate models, but with HRs below 1.38 per interquartile range. Three scores were predictors of shorter RFS, one of shorter SAR. Each RS could only marginally improve an RFS or OS model with the known factors T-stage, N-stage, and microsatellite instability (MSI) status (AUC gains < 0.025 units). The pairwise interscore discordance was never high (maximal Spearman correlation = 0.563) A combined score showed a trend to higher prognostic value and higher AUC increase for OS (HR = 1.74, 95% confidence interval [CI] = 1.44 to 2.10, P < .001, AUC from 0.6918 to 0.7321) and RFS (HR = 1.56, 95% CI = 1.33 to 1.84, P < .001, AUC from 0.6723 to 0.6945) than any single score. CONCLUSIONS: The four tested gene expression-based risk scores provide prognostic information but contribute only marginally to improving models based on established risk factors. A combination of the risk scores might provide more robust information. Predictors of RFS and SAR might need to be different.

Causal relationship between obesity and vitamin D status: bi-directional Mendelian randomization analysis of multiple cohorts.

BACKGROUND: Obesity is associated with vitamin D deficiency, and both are areas of active public health concern. We explored the causality and direction of the relationship between body mass index (BMI) and 25-hydroxyvitamin D [25(OH)D] using genetic markers as instrumental variables (IVs) in bi-directional Mendelian randomization (MR) analysis. METHODS AND FINDINGS: We used information from 21 adult cohorts (up to 42,024 participants) with 12 BMI-related SNPs (combined in an allelic score) to produce an instrument for BMI and four SNPs associated with 25(OH)D (combined in two allelic scores, separately for genes encoding its synthesis or metabolism) as an instrument for vitamin D. Regression estimates for the IVs (allele scores) were generated within-study and pooled by meta-analysis to generate summary effects. Associations between vitamin D scores and BMI were confirmed in the Genetic Investigation of Anthropometric Traits (GIANT) consortium (n = 123,864). Each 1 kg/m(2) higher BMI was associated with 1.15% lower 25(OH)D (p = 6.52×10⁻²⁷). The BMI allele score was associated both with BMI (p = 6.30×10⁻⁶²) and 25(OH)D (-0.06% [95% CI -0.10 to -0.02], p = 0.004) in the cohorts that underwent meta-analysis. The two vitamin D allele scores were strongly associated with 25(OH)D (p≤8.07×10⁻⁵⁷ for both scores) but not with BMI (synthesis score, p = 0.88; metabolism score, p = 0.08) in the meta-analysis. A 10% higher genetically instrumented BMI was associated with 4.2% lower 25(OH)D concentrations (IV ratio: -4.2 [95% CI -7.1 to -1.3], p = 0.005). No association was seen for genetically instrumented 25(OH)D with BMI, a finding that was confirmed using data from the GIANT consortium (p≥0.57 for both vitamin D scores). CONCLUSIONS: On the basis of a bi-directional genetic approach that limits confounding, our study suggests that a higher BMI leads to lower 25(OH)D, while any effects of lower 25(OH)D increasing BMI are likely to be small. Population level interventions to reduce BMI are expected to decrease the prevalence of vitamin D deficiency.

Growth Arrest-Specific Gene 6 product modulates innate immunity in sepsis

Background: Growth Arrest-Specific Gene 6 product (Gas6) is, like anticoagulant protein C, a vitamin K-dependent protein. Our aim was to determine whether Gas6 plays a role in sepsis. Materials and methods: We submitted mice lacking Gas6 (Gas6)/)) or one of its receptors (Axl)/), Tyro3)/) or Mertk)/)) to LPS-induced endotoxemia and peritonitis (cecal ligation and puncture (CLP) and inoculation of E. coli). In addition, we measured Gas6 or its soluble receptors in plasma of eight volunteers that received LPS, 13 healthy subjects, 28 patients with severe sepsis, and 18 patients with non-infectious inflammatory diseases. Results: Gas6 and its soluble receptor sAxl raised in mice models and TNF-a was more elevated in Gas6)/) mice than in wild-type (WT). Protein array showed that before and after LPS injection, titers of 62 cytokines were more elevated in plasma of Gas6)/) than WT mice. Endotoxemia-induced mortality was higher in Gas6)/), Axl)/), Tyro3)/) and Mertk)/) compared to WT mice and mortality subsequent to CLP was amplified in Gas6)/) mice. LPS-stimulated Gas6)/) macrophages produced more cytokines than WT macrophages. This production was dampened by recombinant Gas6. Phosphorylation of Akt in Gas6)/) macrophages was reduced, but p38 phosphorylation and NF-jB translocation were increased. In human, Gas6 raised in plasma after LPS (2 ng/kg). Gas6 and sAxl were higher in patients with severe sepsis than in healthy subjects or control patients, and there was a non-significant trend for higher Gas6 in the survival group. Conclusions: Our data point to Gas6 as a major modulator of innate immunity and provide thereby novel insights into the mechanism of sepsis. Thus Gas6 and its receptors might constitute potential therapeutic targets for the development of new immunomodulating drugs.

Comparative protein profiling identifies elongation factor-1beta and tryparedoxin peroxidase as factors associated with metastasis in Leishmania guyanensis.

Parasites of the Leishmania Viannia subgenus are major causative agents of mucocutaneous leishmaniasis (MCL), a disease characterised by parasite dissemination (metastasis) from the original cutaneous lesion to form debilitating secondary lesions in the nasopharyngeal mucosa. We employed a protein profiling approach to identify potential metastasis factors in laboratory clones of L. (V.) guyanensis with stable phenotypes ranging from highly metastatic (M+) through infrequently metastatic (M+/M-) to non-metastatic (M-). Comparison of the soluble proteomes of promastigotes by two-dimensional electrophoresis revealed two abundant protein spots specifically associated with M+ and M+/M- clones (Met2 and Met3) and two others exclusively expressed in M- parasites (Met1 and Met4). The association between clinical disease phenotype and differential expression of Met1-Met4 was less clear in L. Viannia strains from mucosal (M+) or cutaneous (M-) lesions of patients. Identification of Met1-Met4 by biological mass spectrometry (LC-ES-MS/MS) and bioinformatics revealed that M+ and M- clones express distinct acidic and neutral isoforms of both elongation factor-1 subunit beta (EF-1beta) and cytosolic tryparedoxin peroxidase (TXNPx). This interchange of isoforms may relate to the mechanisms by which the activities of EF-1beta and TXNPx are modulated, and/or differential post-translational modification of the gene product(s). The multiple metabolic functions of EF-1 and TXNPx support the plausibility of their participation in parasite survival and persistence and thereby, metastatic disease. Both polypeptides are active in resistance to chemical and oxidant stress, providing a basis for further elucidation of the importance of antioxidant defence in the pathogenesis underlying MCL.

Identification of CT46/HORMAD1, an immunogenic cancer/testis antigen encoding a putative meiosis-related protein.

Transcripts with ESTs derived exclusively or predominantly from testis, and not from other normal tissues, are likely to be products of genes with testis-restricted expression, and are thus potential cancer/testis (CT) antigen genes. A list of 371 genes with such characteristics was compiled by analyzing publicly available EST databases. RT-PCR analysis of normal and tumor tissues was performed to validate an initial selection of 20 of these genes. Several new CT and CT-like genes were identified. One of these, CT46/HORMAD1, is expressed strongly in testis and weakly in placenta; the highest level of expression in other tissues is &lt;1% of testicular expression. The CT46/HORMAD1 gene was expressed in 31% (34/109) of the carcinomas examined, with 11% (12/109) showing expression levels &gt;10% of the testicular level of expression. CT46/HORMAD1 is a single-copy gene on chromosome 1q21.3, encoding a putative protein of 394 aa. Conserved protein domain analysis identified a HORMA domain involved in chromatin binding. The CT46/HORMAD1 protein was found to be homologous to the prototype HORMA domain-containing protein, Hop1, a yeast meiosis-specific protein, as well as to asy1, a meiotic synaptic mutant protein in Arabidopsis thaliana.

Genome-wide arrays in routine diagnostics of hematological malignancies.

Over the last three decades, cytogenetic analysis of malignancies has become an integral part of disease evaluation and prediction of prognosis or responsiveness to therapy. In most diagnostic laboratories, conventional karyotyping, in conjunction with targeted fluorescence in situ hybridization analysis, is routinely performed to detect recurrent aberrations with prognostic implications. However, the genetic complexity of cancer cells requires a sensitive genome-wide analysis, enabling the detection of small genomic changes in a mixed cell population, as well as of regions of homozygosity. The advent of comprehensive high-resolution genomic tools, such as molecular karyotyping using comparative genomic hybridization or single-nucleotide polymorphism microarrays, has overcome many of the limitations of traditional cytogenetic techniques and has been used to study complex genomic lesions in, for example, leukemia. The clinical impact of the genomic copy-number and copy-neutral alterations identified by microarray technologies is growing rapidly and genome-wide array analysis is evolving into a diagnostic tool, to better identify high-risk patients and predict patients' outcomes from their genomic profiles. Here, we review the added clinical value of an array-based genome-wide screen in leukemia, and discuss the technical challenges and an interpretation workflow in applying arrays in the acquired cytogenetic diagnostic setting.

Local influence for spatial analysis of soil physical properties and soybean yield using student's t-distribution

The modeling and estimation of the parameters that define the spatial dependence structure of a regionalized variable by geostatistical methods are fundamental, since these parameters, underlying the kriging of unsampled points, allow the construction of thematic maps. One or more atypical observations in the sample data can affect the estimation of these parameters. Thus, the assessment of the combined influence of these observations by the analysis of Local Influence is essential. The purpose of this paper was to propose local influence analysis methods for the regionalized variable, given that it has n-variate Student's t-distribution, and compare it with the analysis of local influence when the same regionalized variable has n-variate normal distribution. These local influence analysis methods were applied to soil physical properties and soybean yield data of an experiment carried out in a 56.68 ha commercial field in western Paraná, Brazil. Results showed that influential values are efficiently determined with n-variate Student's t-distribution.

Associations of serum EBV DNA and gammopathy with post-transplant lymphoproliferative disease.

BACKGROUND: Post-transplant lymphoproliferative disease (PTLD) is a life-threatening complication of immunosuppression following transplantation. Epstein-Barr virus (EBV) and gammopathy in serum are associated with PTLD, but these two parameters have not been evaluated in parallel for their association with PTLD. METHODS: We evaluated the incidence of EBV load positivity, gammopathy, and protein expression in sera from all PTLD patients diagnosed at our hospital during the past seven yr. Results were compared with those of a control group including matched transplanted patients who did not develop PTLD. RESULTS: Seven of 10 PTLD patients presented EBV(+) PTLD, for which five patients had detectable serum EBV DNA levels compared with none of 38 controls (RR between two groups =121, p &lt; 0.0001). Five out of 10 patients had gammopathy at PTLD diagnosis compared with 5/38 controls (RR between two groups = 6.6, p = 0.022). Additionally, protein serum analysis by high-resolution two-dimensional gel electrophoresis and image examination failed to evidence specific abnormality in patients with PTLD compared with controls. CONCLUSIONS: Our results confirm an association between EBV in sera and gammopathy with PTLD, and highlight the high specificity of the former analysis. Whether a combination of both analyses will improve the clinical detection of PTLD remains to be evaluated in a larger prospective cohort study.

Bioinformatics-driven identification and examination of candidate genes for non-alcoholic fatty liver disease.

ObjectiveCandidate genes for non-alcoholic fatty liver disease (NAFLD) identified by a bioinformatics approach were examined for variant associations to quantitative traits of NAFLD-related phenotypes.Research Design and MethodsBy integrating public database text mining, trans-organism protein-protein interaction transferal, and information on liver protein expression a protein-protein interaction network was constructed and from this a smaller isolated interactome was identified. Five genes from this interactome were selected for genetic analysis. Twenty-one tag single-nucleotide polymorphisms (SNPs) which captured all common variation in these genes were genotyped in 10,196 Danes, and analyzed for association with NAFLD-related quantitative traits, type 2 diabetes (T2D), central obesity, and WHO-defined metabolic syndrome (MetS).Results273 genes were included in the protein-protein interaction analysis and EHHADH, ECHS1, HADHA, HADHB, and ACADL were selected for further examination. A total of 10 nominal statistical significant associations (P<0.05) to quantitative metabolic traits were identified. Also, the case-control study showed associations between variation in the five genes and T2D, central obesity, and MetS, respectively. Bonferroni adjustments for multiple testing negated all associations.ConclusionsUsing a bioinformatics approach we identified five candidate genes for NAFLD. However, we failed to provide evidence of associations with major effects between SNPs in these five genes and NAFLD-related quantitative traits, T2D, central obesity, and MetS.

Molecular clock is involved in predictive circadian adjustment of renal function.

Renal excretion of water and major electrolytes exhibits a significant circadian rhythm. This functional periodicity is believed to result, at least in part, from circadian changes in secretion/reabsorption capacities of the distal nephron and collecting ducts. Here, we studied the molecular mechanisms underlying circadian rhythms in the distal nephron segments, i.e., distal convoluted tubule (DCT) and connecting tubule (CNT) and the cortical collecting duct (CCD). Temporal expression analysis performed on microdissected mouse DCT/CNT or CCD revealed a marked circadian rhythmicity in the expression of a large number of genes crucially involved in various homeostatic functions of the kidney. This analysis also revealed that both DCT/CNT and CCD possess an intrinsic circadian timing system characterized by robust oscillations in the expression of circadian core clock genes (clock, bma11, npas2, per, cry, nr1d1) and clock-controlled Par bZip transcriptional factors dbp, hlf, and tef. The clock knockout mice or mice devoid of dbp/hlf/tef (triple knockout) exhibit significant changes in renal expression of several key regulators of water or sodium balance (vasopressin V2 receptor, aquaporin-2, aquaporin-4, alphaENaC). Functionally, the loss of clock leads to a complex phenotype characterized by partial diabetes insipidus, dysregulation of sodium excretion rhythms, and a significant decrease in blood pressure. Collectively, this study uncovers a major role of molecular clock in renal function.

Spatiotemporal analysis of multichannel EEG: CARTOOL.

This paper describes methods to analyze the brain's electric fields recorded with multichannel Electroencephalogram (EEG) and demonstrates their implementation in the software CARTOOL. It focuses on the analysis of the spatial properties of these fields and on quantitative assessment of changes of field topographies across time, experimental conditions, or populations. Topographic analyses are advantageous because they are reference independents and thus render statistically unambiguous results. Neurophysiologically, differences in topography directly indicate changes in the configuration of the active neuronal sources in the brain. We describe global measures of field strength and field similarities, temporal segmentation based on topographic variations, topographic analysis in the frequency domain, topographic statistical analysis, and source imaging based on distributed inverse solutions. All analysis methods are implemented in a freely available academic software package called CARTOOL. Besides providing these analysis tools, CARTOOL is particularly designed to visualize the data and the analysis results using 3-dimensional display routines that allow rapid manipulation and animation of 3D images. CARTOOL therefore is a helpful tool for researchers as well as for clinicians to interpret multichannel EEG and evoked potentials in a global, comprehensive, and unambiguous way.

Concordance among digital gene expression, microarrays, and qPCR when measuring differential expression of microRNAs.

Profiling microRNA (miRNA) expression is of widespread interest given the critical role of miRNAs in many cellular functions. Profiling can be achieved via hybridization-based (microarrays), sequencing-based, or amplification-based (quantitative reverse transcription-PCR, qPCR) technologies. Among these, microarrays face the significant challenge of accurately distinguishing between mature and immature miRNA forms, and different vendors have developed different methods to meet this challenge. Here we measure differential miRNA expression using the Affymetrix, Agilent, and Illumina microarray platforms, as well as qPCR (Applied Biosystems) and ultra high-throughput sequencing (Illumina). We show that the differential expression measurements are more divergent when the three types of microarrays are compared than when the Agilent microarray, qPCR, and sequencing technology measurements are compared, which exhibit a good overall concordance.