Statistical models for haplotype sharing in case-parent trio data

BACKGROUND: Haplotype sharing statistics have been introduced in an ad-hoc way, often relying heavily on permutation testing. As a result, applying these approaches to whole genome association studies or to evaluate their properties in extensive simulation experiments is problematic. Further, permutation testing may be inappropriate in the presence of phase ambiguity and population stratification. AIMS: To present a simple framework for a class of haplotype sharing statistics useful for association mapping in case-parent trio data. This framework allows derivation of novel haplotype sharing tests as well as simple variance estimators and asymptotic distributions for haplotype sharing tests. RESULTS AND CONCLUSIONS: We validated that our approach is appropriately sized using simulated data, and illustrate the methodology by analyzing a Crohn's disease dataset. We find that haplotype-based analyses are much more powerful than single-locus analyses for these data.     

Detection rates for genotyping errors in SNPs using the trio design

One well-known approach for the analysis of transmission-disequilibrium is the investigation of single nucleotide polymorphisms (SNPs) in trios consisting of an affected child and its parents. Results may be biased by erroneously given genotypes. Various reasons, among them sample swap or wrong pedigree structure, represent a possible source for biased results. As these can be partly ruled out by good study conditions together with checks for correct pedigree structure by a series of independent markers, the remaining main cause for errors is genotyping errors. Some of the errors can be detected by Mendelian checks whilst others are compatible with the pedigree structure. The extent of genotyping errors can be estimated by investigating the rate of detected genotyping errors by Mendelian checks. In many studies only one SNP of a specific genomic region is investigated by TDT which leaves Mendelian checks as the only tool to control genotyping errors. From the rate of detected errors the true error rate can be estimated. Gordon et al. [Hum Hered 1999;49:65-70] considered the case of genotyping errors that occur randomly and independently with some fixed probability for the wrong ascertainment of an allele. In practice, instead of single alleles, SNP genotypes are determined. Therefore, we study the proportion of detected errors (detection rate) based on genotypes. In contrast to Gordon et al., who reported detection rates between 25 and 30%, we obtain higher detection rates ranging from 39 up to 61% considering likely error structures in the data. We conclude that detection rates are probably substantially higher than those reported by Gordon et al.     

Conceptual approach to renewable barrier film design based on wood hydrolysate

Biomass is converted to oxygen barriers through a conceptually unconventional approach involving the preservation of the biomass native interactions and macromolecular components and enhancing the effect by created interactions with a co-component. A combined calculation/assessment model is elaborated to understand, quantify, and predict which compositions that provide an intermolecular affinity high enough to mediate the molecular packing needed to create a functioning barrier. The biomass used is a wood hydrolysate, a polysaccharide-rich but not highly refined mixture where a fair amount of the native intermolecular and intramolecular hemicelluloses-lignin interactions are purposely preserved, resulting in barriers with very low oxygen permeabilities (OP) both at 50 and 80% relative humidity and considerably lower OPs than coatings based on the corresponding highly purified spruce hemicellulose, O-acetyl galactoglucomannan (AcGGM). The component interactions and mutual affinities effectively mediate an immobilization of the chain segments in a dense disordered structure, modeled through the Hansen's solubility parameter concept and quantified on the nanolength scale by positron annihilation lifetime spectrum (PALS).     

The trio guanine nucleotide exchange factor is a RhoA target. Binding of RhoA to the trio immunoglobulin-like domain

Trio is a complex protein containing two guanine nucleotide exchange factor domains each with associated pleckstrin homology domains, a serine/threonine kinase domain, two SH3 domains, an immunoglobulin-like domain, and spectrin-like repeats. Trio was originally identified as a LAR tyrosine phosphatase-binding protein and is involved in actin remodeling, cell migration, and cell growth. Herein we provide evidence that Trio not only activates RhoA but is also a RhoA target. The RhoA-binding site was mapped to the Trio immunoglobulin-like domain. RhoA isoprenylation is necessary for the RhoA-Trio interaction, because mutation of the RhoA carboxyl-terminal cysteine residue blocked binding. The existence of an intramolecular functional link between RhoA activation and RhoA binding is suggested by the finding that Trio exchange activity enhanced RhoA binding to Trio. Furthermore, immunofluorescence studies of HeLa cells showed that although ectopically expressed Trio was evenly distributed within the cell, co-expression of Trio with RhoA resulted in relocalization of Trio into punctate structures. Relocalization was not observed with Trio constructs lacking the immunoglobulin-like domain, indicating that RhoA acts to regulate Trio localization via binding to the immunoglobulin-like domain. We propose that Trio-mediated RhoA activation and subsequent RhoA-mediated relocalization of Trio functions to modulate and coordinate Trio signaling.     

Confidence intervals for genotype relative risks and allele frequencies from the case parent trio design for candidate-gene studies

OBJECTIVES: Confidence intervals for genotype relative risks, for allele frequencies and for the attributable risk in the case parent trio design for candidate-gene studies are proposed which can be easily calculated from the observed familial genotype frequencies. METHODS: Likelihood theory and the delta method were used to derive point estimates and confidence internals. We used Monte Carlo simulations to show the validity of the formulae for a variety of given modes of inheritance and allele frequencies and illustrated their usefulness by applying them to real data. RESULTS: Generally these formulae were found to be valid for 'sufficiently large' sample sizes. For smaller sample sizes the estimators for genotype relative risks tended to be conservative whereas the estimator for attributable risk was found to be anti-conservative for moderate to high allele frequencies. CONCLUSIONS: Since the proposed formulae provide quantitative information on the individual and epidemiological relevance of a genetic variant they might be a useful addition to the traditional statistical significance level of TDT results.     

De novo design of VEGFR-2 tyrosine kinase inhibitors based on a linked-fragment approach

Vascular endothelial growth factor receptor-2 (VEGFR-2) tyrosine kinase inhibitors have been demonstrated to possess substantial antitumor activity. VEGFR-2 tyrosine kinase inhibitors are crucial for development of antitumor drugs. Based on the crystal structure of VEGFR-2 tyrosine kinase, a linked-fragment strategy was employed to design novel VEGFR-2 tyrosine kinase inhibitors, and 1000 compounds were generated in this process. Absorption, distribution, metabolism, excretion and toxicity (ADMET) were used to screen the 1000 compounds, and 59 compounds were acceptable. Scaffold hopping was then used for further screening, and only four compounds were obtained in this way. Then, the binding energy of the four molecules to VEGFR-2 tyrosine kinase was calculated using molecular docking, and their values were found to be lower than that of Sorafenib. Finally, molecular dynamics simulations were performed on the complex of the compound with the lowest binding energy with VEGFR-2 tyrosine kinase, and the binding model was analyzed. At the end, four chemical entities with novel structures were obtained, and were suggested for experimental testing in future studies.     

Assessing overfishing based on the distance-to-target approach

The International Journal of Life Cycle Assessment - Overfishing has been a global challenge for several decades with severe impacts on biodiversity and ecosystem services. Several approaches for...     

Molecular drug targets and structure based drug design: A holistic approach

Access to the complete human genome sequence as well as to the complete sequences of pathogenic organisms provides information that can result in an avalanche of therapeutic targets. Structure-based design is one of the first techniques to be used in drug design. Structure based design refers specifically to finding and complementing the 3D structure (binding and/or active site) of a target molecule such as a receptor protein. The aim of this review is to give an outline of studies in the field of structure based drug design that has helped in the discovery process of new drugs. The emphasis will be on comparative/homology modeling.     

Multipoint linkage analysis using sib pairs: an interval mapping approach for dichotomous outcomes.

I propose an interval mapping approach suitable for a dichotomous outcome, with emphasis on samples of affected sib pairs. The method computes a lod score for each of a set of locations in the interval between two flanking markers and takes as its estimate of trait-locus location the maximum lod score in the interval, provided it exceeds the prespecified critical value. Use of the method depends on prior knowledge of the genetic model for the disease only through available estimates of recurrence risk to relatives of affected individuals. The method gives an unbiased estimate of location, provided the recurrence risk are correctly specified and provided the marker identity-by-descent probabilities are jointly, rather than individually, estimated. I also discuss use of the method for traits determined by two loci and give an approximation that has good power for a wide range of two-locus models.     

The many faces of the guanine-nucleotide exchange factor trio

Small Rho-GTPases are enzymes that are bound to GDP or GTP, which determines their inactive or active state, respectively. The exchange of GDP for GTP is catalyzed by so-called Rho-guanine nucleotide exchange factors (GEFs). Rho-GEFs are characterized by a Dbl-homology (DH) and adjacent Pleckstrin-homology (PH) domain that serves as enzymatic unit for the GDP/GTP exchange. Rho-GEFs show different GTPase specificities, meaning that a particular GEF can activate either multiple GTPases or only one specific GTPase. We recently reported that the Rho-GEF Trio, known to be able to exchange GTP on Rac1, RhoG and RhoA, regulates lamellipodia formation to mediate cell spreading and migration in a Rac1-dependent manner. In this commentary, we review the current knowledge of Trio in several aspects of cell biology.     

The many faces of the guanine-nucleotide exchange factor trio

Small Rho-GTPases are enzymes that are bound to GDP or GTP, which determines their inactive or active state, respectively. The exchange of GDP for GTP is catalyzed by so-called Rho-guanine nucleotide exchange factors (GEFs). Rho-GEFs are characterized by a Dbl-homology (DH) and adjacent Pleckstrin-homology (PH) domain that serves as enzymatic unit for the GDP/GTP exchange. Rho-GEFs show different GTPase specificities, meaning that a particular GEF can activate either multiple GTPases or only one specific GTPase. We recently reported that the Rho-GEF Trio, known to be able to exchange GTP on Rac1, RhoG and RhoA, regulates lamellipodia formation to mediate cell spreading and migration in a Rac1-dependent manner. In this commentary, we review the current knowledge of Trio in several aspects of cell biology.     

Protein sequence comparison based on the wavelet transform approach

A protein's chemical properties, the chain conformation, the function of the protein and its species specificity are determined by the information contained in the amino acid sequence. Proteins of similar functions have at some level sequential identical amino acid sequences. The closer the phylogenetic relationship, the more similar are the sequences. To find the similarities between two or more protein sequences is of great importance for protein sequence analysis. The differences in the amino acid sequences permit the construction of a family tree of evolution. In this work, a comparison method was devised that is capable of analysing a protein sequence 'hierarchically', i.e. it can examine a protein sequence at different spatial resolutions. Based on a wavelet decomposition of protein sequences and a cross-correlation study, a sequence-scale similarity concept is proposed for generating a similarity vector, which renders the comparison of two sequences feasible at different spatial resolutions (scales). This new similarity concept is an expansion of the conventional sequence similarity, which only takes into account the local pairwise amino acid match and ignores the information contained in coarser spatial resolutions.     

Multipoint linkage detection in the presence of heterogeneity

Linkage heterogeneity is common for complex diseases. It is well known that loss of statistical power for detecting linkage will result if one assumes complete homogeneity in the presence of linkage heterogeneity. To this end, Smith (1963, Annals of Human Genetics 27, 175-182) proposed an admixture model to account for linkage heterogeneity. It is well known that for this model, the conventional chi-squared approximation to the likelihood ratio test for no linkage does not apply even when the sample size is large. By dealing with nuclear families and one marker at a time for genetic diseases with simple modes of inheritance, score-based test statistics (Liang and Rathouz, 1999, Biometrics 55, 65-74) and likelihood-ratio-based test statistics (Lemdani and Pons, 1995, Biometrics 51, 1033-1041) have been proposed which have a simple large-sample distribution under the null hypothesis of linkage. In this paper, we extend their work to more practical situations that include information from multiple markers and multi-generational pedigrees while allowing for a class of general genetic models. Three different approaches are proposed to eliminate the nuisance parameters in these test statistics. We show that all three approaches lead to the same asymptotic distribution under the null hypothesis of no linkage. Simulation results show that the proposed test statistics have adequate power to detect linkage and that the performances of these two classes of test statistics are quite comparable. We have applied the proposed method to a family study of asthma (Barnes et al., 1996), in which the score-based test shows evidence of linkage with p-value <0.0001 in the region of interest on chromosome 12. Additionally, we have implemented this score-based test within the frequently used computer package GENEHUNTER.     

An LMI approach to design H(infinity) controllers for discrete-time nonlinear systems based on unified models

A unified neural network model termed standard neural network model (SNNM) is advanced. Based on the robust L(2) gain (i.e. robust H(infinity) performance) analysis of the SNNM with external disturbances, a state-feedback control law is designed for the SNNM to stabilize the closed-loop system and eliminate the effect of external disturbances. The control design constraints are shown to be a set of linear matrix inequalities (LMIs) which can be easily solved by various convex optimization algorithms (e.g. interior-point algorithms) to determine the control law. Most discrete-time recurrent neural network (RNNs) and discrete-time nonlinear systems modelled by neural networks or Takagi and Sugeno (T-S) fuzzy models can be transformed into the SNNMs to be robust H(infinity) performance analyzed or robust H(infinity) controller synthesized in a unified SNNM's framework. Finally, some examples are presented to illustrate the wide application of the SNNMs to the nonlinear systems, and the proposed approach is compared with related methods reported in the literature.     

A new approach to the design of hybrid hybridomas based on the use of an actinomycin D-resistant line of murine myeloma]

The hybrid hybridomas (tetradomas) were produced from the fusion of the double mutant actinomycin Dr (ADr)/HATs hybridoma to horseradish peroxidase (HRP) and wild type hybridoma to alpha-endorphin (EP). The double mutant phenotype was constructed using the new strategy, based on the fusion of immune mouse splenocytes with mouse myeloma (X63.Ag8, 653) cell variants, made resistant to 30 ng/ml of AD by stepwise selection. This allowed the direct introduction of the dominant selective marker (ADr) into the hybrid cells. Tetradomas secreted the bispecific monoclonal antibodies (bi Mabs), simultaneously binding to EP and HRP in double antigen ELISA, the ELISA plates covered with EP-bovine serum albumin conjugate. Using rat pituitary the bi Mabs were shown to be effective for immunostaining of EP-producing cells. EP-producing cells.     

Cancer therapy design based on pathway logic

MOTIVATION: Cancer encompasses various diseases associated with loss of cell cycle control, leading to uncontrolled cell proliferation and/or reduced apoptosis. Cancer is usually caused by malfunction(s) in the cellular signaling pathways. Malfunctions occur in different ways and at different locations in a pathway. Consequently, therapy design should first identify the location and type of malfunction to arrive at a suitable drug combination. RESULTS: We consider the growth factor (GF) signaling pathways, widely studied in the context of cancer. Interactions between different pathway components are modeled using Boolean logic gates. All possible single malfunctions in the resulting circuit are enumerated and responses of the different malfunctioning circuits to a 'test' input are used to group the malfunctions into classes. Effects of different drugs, targeting different parts of the Boolean circuit, are taken into account in deciding drug efficacy, thereby mapping each malfunction to an appropriate set of drugs.     

Multipoint mapping studies of six loci on chromosome 11

The six loci, beta-globin (HBBC), parathyroid hormone (PTH), oncogene c-Ha-ras-1 (HRAS1), insulin (INS), calcitonin (CAL) and catalase (CAT) loci, have been mapped to 11p in the order: CAT-CAL-PTH-HBBC-(HRAS1-INS). The purpose of the current study was to examine the linkage relationships, especially the multipoint relationships of these loci in detail. In the 18 families studied, a significant sex difference in recombination was found for the HBBC: HRAS1 linkage with more recombination in the male parent than the female parent (22 vs. 2%). The results of the multipoint analyses provided further evidence for the order CAT-CAL-PTH-HBBC-(HRAS1-INS); however, the order of the last two tightly linked loci is still not clear.