Robust regression in biological assay: application to the evaluation of alternative experimental techniques.

Robust Huber type regression and testing of linear hypotheses are adapted to statistical analysis of parallel line and slope ratio assays. They are applied in the evaluation of results of several experiments carried out in order to compare and validate alternatives to animal experimentation based on embryo and cell cultures. Computational procedures necessary for the application of robust methods of analysis used the conversational statistical package ROBSYS. Special commands for the analysis of parallel line and slope ratio assays have been added to ROBSYS.

Mutation analysis of genes that control the G1/S cell cycle in melanoma: TP53, CDKN1A, CDKN2A, and CDKN2B.

BACKGROUND The role of genes involved in the control of progression from the G1 to the S phase of the cell cycle in melanoma tumors in not fully known. The aim of our study was to analyse mutations in TP53, CDKN1A, CDKN2A, and CDKN2B genes in melanoma tumors and melanoma cell lines METHODS We analysed 39 primary and metastatic melanomas and 9 melanoma cell lines by single-stranded conformational polymorphism (SSCP). RESULTS The single-stranded technique showed heterozygous defects in the TP53 gene in 8 of 39 (20.5%) melanoma tumors: three new single point mutations in intronic sequences (introns 1 and 2) and exon 10, and three new single nucleotide polymorphisms located in introns 1 and 2 (C to T transition at position 11701 in intron 1; C insertion at position 11818 in intron 2; and C insertion at position 11875 in intron 2). One melanoma tumor exhibited two heterozygous alterations in the CDKN2A exon 1 one of which was novel (stop codon, and missense mutation). No defects were found in the remaining genes. CONCLUSION These results suggest that these genes are involved in melanoma tumorigenesis, although they may be not the major targets. Other suppressor genes that may be informative of the mechanism of tumorigenesis in skin melanomas should be studied.

An R Library for Compositional Data Analysis in Archaeometry

Compositional data naturally arises from the scientific analysis of the chemicalcomposition of archaeological material such as ceramic and glass artefacts. Data of thistype can be explored using a variety of techniques, from standard multivariate methodssuch as principal components analysis and cluster analysis, to methods based upon theuse of log-ratios. The general aim is to identify groups of chemically similar artefactsthat could potentially be used to answer questions of provenance.This paper will demonstrate work in progress on the development of a documentedlibrary of methods, implemented using the statistical package R, for the analysis ofcompositional data. R is an open source package that makes available very powerfulstatistical facilities at no cost. We aim to show how, with the aid of statistical softwaresuch as R, traditional exploratory multivariate analysis can easily be used alongside, orin combination with, specialist techniques of compositional data analysis.The library has been developed from a core of basic R functionality, together withpurpose-written routines arising from our own research (for example that reported atCoDaWork'03). In addition, we have included other appropriate publicly availabletechniques and libraries that have been implemented in R by other authors. Availablefunctions range from standard multivariate techniques through to various approaches tolog-ratio analysis and zero replacement. We also discuss and demonstrate a smallselection of relatively new techniques that have hitherto been little-used inarchaeometric applications involving compositional data. The application of the libraryto the analysis of data arising in archaeometry will be demonstrated; results fromdifferent analyses will be compared; and the utility of the various methods discussed

Compositional data analysis in archaeometry

We shall call an n × p data matrix fully-compositional if the rows sum to a constant, and sub-compositional if the variables are a subset of a fully-compositional data set1. Such data occur widely in archaeometry, where it is common to determine the chemical composition of ceramic, glass, metal or other artefacts using techniques such as neutron activation analysis (NAA), inductively coupled plasma spectroscopy (ICPS), X-ray fluorescence analysis (XRF) etc. Interest often centres on whether there are distinct chemical groups within the data and whether, for example, these can be associated with different origins or manufacturing technologies

Exploration of geological variability and possible processes through the use of compositional data analysis: an example using scottish metamorphosed

Developments in the statistical analysis of compositional data over the last twodecades have made possible a much deeper exploration of the nature of variability,and the possible processes associated with compositional data sets from manydisciplines. In this paper we concentrate on geochemical data sets. First we explainhow hypotheses of compositional variability may be formulated within the naturalsample space, the unit simplex, including useful hypotheses of subcompositionaldiscrimination and specific perturbational change. Then we develop through standardmethodology, such as generalised likelihood ratio tests, statistical tools to allow thesystematic investigation of a complete lattice of such hypotheses. Some of these tests are simple adaptations of existing multivariate tests but others require specialconstruction. We comment on the use of graphical methods in compositional dataanalysis and on the ordination of specimens. The recent development of the conceptof compositional processes is then explained together with the necessary tools for astaying- in-the-simplex approach, namely compositional singular value decompositions. All these statistical techniques are illustrated for a substantial compositional data set, consisting of 209 major-oxide and rare-element compositions of metamorphosed limestones from the Northeast and Central Highlands of Scotland.Finally we point out a number of unresolved problems in the statistical analysis ofcompositional processes

Compositional Data Analysis with R

R from http://www.r-project.org/ is ‘GNU S’ – a language and environment for statistical computingand graphics. The environment in which many classical and modern statistical techniques havebeen implemented, but many are supplied as packages. There are 8 standard packages and many moreare available through the cran family of Internet sites http://cran.r-project.org .We started to develop a library of functions in R to support the analysis of mixtures and our goal isa MixeR package for compositional data analysis that provides support foroperations on compositions: perturbation and power multiplication, subcomposition with or withoutresiduals, centering of the data, computing Aitchison’s, Euclidean, Bhattacharyya distances,compositional Kullback-Leibler divergence etc.graphical presentation of compositions in ternary diagrams and tetrahedrons with additional features:barycenter, geometric mean of the data set, the percentiles lines, marking and coloring ofsubsets of the data set, theirs geometric means, notation of individual data in the set . . .dealing with zeros and missing values in compositional data sets with R procedures for simpleand multiplicative replacement strategy,the time series analysis of compositional data.We’ll present the current status of MixeR development and illustrate its use on selected data sets

Analysis of CXCL12 3 ' UTR G > A polymorphism in colorectal cancer

Colorectal cancer is one of the most prevalent cancers in developed countries. However, the genetic factors influencing its appearance remain far from being fully characterized. Recently, a G>A functional transition mapping the 3' untranslated region of the CXCL12 gene (rs1801157) has been found to be under-represented among rectal cancer patients when compared to colon cancer patients from a Swedish series. Here we present the results from an independent analysis of CXCL12 rs1801157 in a larger CRC series of Spanish origin in order to analyse the robustness of this association within a different European population. No significant difference was observed between controls and colon or rectal cancer patients. We were also unable to find a correlation between rs1801157 and different prognostic markers such as metastasis development or disease-free survival time. The epidemiologic data involving CXCL12 rs1801157 in colorectal cancer risk are discussed.

Methods for the ex vivo characterization of human CD8+ T subsets based on gene expression and replicative history analysis.

The generation of an antigen-specific T-lymphocyte response is a complex multi-step process. Upon T-cell receptor-mediated recognition of antigen presented by activated dendritic cells, naive T-lymphocytes enter a program of proliferation and differentiation, during the course of which they acquire effector functions and may ultimately become memory T-cells. A major goal of modern immunology is to precisely identify and characterize effector and memory T-cell subpopulations that may be most efficient in disease protection. Sensitive methods are required to address these questions in exceedingly low numbers of antigen-specific lymphocytes recovered from clinical samples, and not manipulated in vitro. We have developed new techniques to dissect immune responses against viral or tumor antigens. These allow the isolation of various subsets of antigen-specific T-cells (with major histocompatibility complex [MHC]-peptide multimers and five-color FACS sorting) and the monitoring of gene expression in individual cells (by five-cell reverse transcription-polymerase chain reaction [RT-PCR]). We can also follow their proliferative life history by flow-fluorescence in situ hybridization (FISH) analysis of average telomere length. Recently, using these tools, we have identified subpopulations of CD8+ T-lymphocytes with distinct proliferative history and partial effector-like properties. Our data suggest that these subsets descend from recently activated T-cells and are committed to become differentiated effector T-lymphocytes.

Malaria diagnosis from pooled blood samples: comparative analysis of real-time PCR, nested PCR and immunoassay as a platform for the molecular and serological diagnosis of malaria on a large-scale

Malaria diagnoses has traditionally been made using thick blood smears, but more sensitive and faster techniques are required to process large numbers of samples in clinical and epidemiological studies and in blood donor screening. Here, we evaluated molecular and serological tools to build a screening platform for pooled samples aimed at reducing both the time and the cost of these diagnoses. Positive and negative samples were analysed in individual and pooled experiments using real-time polymerase chain reaction (PCR), nested PCR and an immunochromatographic test. For the individual tests, 46/49 samples were positive by real-time PCR, 46/49 were positive by nested PCR and 32/46 were positive by immunochromatographic test. For the assays performed using pooled samples, 13/15 samples were positive by real-time PCR and nested PCR and 11/15 were positive by immunochromatographic test. These molecular methods demonstrated sensitivity and specificity for both the individual and pooled samples. Due to the advantages of the real-time PCR, such as the fast processing and the closed system, this method should be indicated as the first choice for use in large-scale diagnosis and the nested PCR should be used for species differentiation. However, additional field isolates should be tested to confirm the results achieved using cultured parasites and the serological test should only be adopted as a complementary method for malaria diagnosis.

Sources of pre-analytical variations in yield of DNA extracted from blood samples: analysis of 50,000 DNA samples in EPIC.

The European Prospective Investigation into Cancer and nutrition (EPIC) is a long-term, multi-centric prospective study in Europe investigating the relationships between cancer and nutrition. This study has served as a basis for a number of Genome-Wide Association Studies (GWAS) and other types of genetic analyses. Over a period of 5 years, 52,256 EPIC DNA samples have been extracted using an automated DNA extraction platform. Here we have evaluated the pre-analytical factors affecting DNA yield, including anthropometric, epidemiological and technical factors such as center of subject recruitment, age, gender, body-mass index, disease case or control status, tobacco consumption, number of aliquots of buffy coat used for DNA extraction, extraction machine or procedure, DNA quantification method, degree of haemolysis and variations in the timing of sample processing. We show that the largest significant variations in DNA yield were observed with degree of haemolysis and with center of subject recruitment. Age, gender, body-mass index, cancer case or control status and tobacco consumption also significantly impacted DNA yield. Feedback from laboratories which have analyzed DNA with different SNP genotyping technologies demonstrate that the vast majority of samples (approximately 88%) performed adequately in different types of assays. To our knowledge this study is the largest to date to evaluate the sources of pre-analytical variations in DNA extracted from peripheral leucocytes. The results provide a strong evidence-based rationale for standardized recommendations on blood collection and processing protocols for large-scale genetic studies.

Laboratory detection of respiratory viruses by automated techniques.

Advances in clinical virology for detecting respiratory viruses have been focused on nucleic acids amplification techniques, which have converted in the reference method for the diagnosis of acute respiratory infections of viral aetiology. Improvements of current commercial molecular assays to reduce hands-on-time rely on two strategies, a stepwise automation (semi-automation) and the complete automation of the whole procedure. Contributions to the former strategy have been the use of automated nucleic acids extractors, multiplex PCR, real-time PCR and/or DNA arrays for detection of amplicons. Commercial fully-automated molecular systems are now available for the detection of respiratory viruses. Some of them could convert in point-of-care methods substituting antigen tests for detection of respiratory syncytial virus and influenza A and B viruses. This article describes laboratory methods for detection of respiratory viruses. A cost-effective and rational diagnostic algorithm is proposed, considering technical aspects of the available assays, infrastructure possibilities of each laboratory and clinic-epidemiologic factors of the infection.

Direct analysis of dried blood spots coupled with mass spectrometry: concepts and biomedical applications.

Because of the emergence of dried blood spots (DBS) as an attractive alternative to conventional venous plasma sampling in many pharmaceutical companies and clinical laboratories, different analytical approaches have been developed to enable automated handling of DBS samples without any pretreatment. Associated with selective and sensitive MS-MS detection, these procedures give good results in the rapid identification and quantification of drugs (generally less than 3 min total run time), which is desirable because of the high throughput requirements of analytical laboratories. The objective of this review is to describe the analytical concepts of current direct DBS techniques and to present their advantages and disadvantages, with particular focus on automation capacity and commercial availability. Finally, an overview of the different biomedical applications in which these concepts could be of major interest will be presented.

Non-invasive prenatal diagnosis of multiple endocrine neoplasia type 2A using COLD-PCR combined with HRM genotyping analysis from maternal serum.

The multiple endocrine neoplasia type 2A (MEN2A) is a monogenic disorder characterized by an autosomal dominant pattern of inheritance which is characterized by high risk of medullary thyroid carcinoma in all mutation carriers. Although this disorder is classified as a rare disease, the patients affected have a low life quality and a very expensive and continuous treatment. At present, MEN2A is diagnosed by gene sequencing after birth, thus trying to start an early treatment and by reduction of morbidity and mortality. We first evaluated the presence of MEN2A mutation (C634Y) in serum of 25 patients, previously diagnosed by sequencing in peripheral blood leucocytes, using HRM genotyping analysis. In a second step, we used a COLD-PCR approach followed by HRM genotyping analysis for non-invasive prenatal diagnosis of a pregnant woman carrying a fetus with a C634Y mutation. HRM analysis revealed differences in melting curve shapes that correlated with patients diagnosed for MEN2A by gene sequencing analysis with 100% accuracy. Moreover, the pregnant woman carrying the fetus with the C634Y mutation revealed a melting curve shape in agreement with the positive controls in the COLD-PCR study. The mutation was confirmed by sequencing of the COLD-PCR amplification product. In conclusion, we have established a HRM analysis in serum samples as a new primary diagnosis method suitable for the detection of C634Y mutations in MEN2A patients. Simultaneously, we have applied the increase of sensitivity of COLD-PCR assay approach combined with HRM analysis for the non-invasive prenatal diagnosis of C634Y fetal mutations using pregnant women serum.

Comprehensive analysis of NRG1 common and rare variants in Hirschsprung patients.

Hirschsprung disease (HSCR, OMIM 142623) is a developmental disorder characterized by the absence of ganglion cells along variable lengths of the distal gastrointestinal tract, which results in tonic contraction of the aganglionic gut segment and functional intestinal obstruction. The RET proto-oncogene is the major gene for HSCR with differential contributions of its rare and common, coding and noncoding mutations to the multifactorial nature of this pathology. Many other genes have been described to be associated with the pathology, as NRG1 gene (8p12), encoding neuregulin 1, which is implicated in the development of the enteric nervous system (ENS), and seems to contribute by both common and rare variants. Here we present the results of a comprehensive analysis of the NRG1 gene in the context of the disease in a series of 207 Spanish HSCR patients, by both mutational screening of its coding sequence and evaluation of 3 common tag SNPs as low penetrance susceptibility factors, finding some potentially damaging variants which we have functionally characterized. All of them were found to be associated with a significant reduction of the normal NRG1 protein levels. The fact that those mutations analyzed alter NRG1 protein would suggest that they would be related with HSCR disease not only in Chinese but also in a Caucasian population, which reinforces the implication of NRG1 gene in this pathology.

Factors associated with use of community mental health services by schizophrenia patients using multilevel analysis

BACKGROUND Persons with schizophrenia and related disorders may be particularly sensitive to a number of determinants of service use, including those related with illness, socio-demographic characteristics and organizational factors. The objective of this study is to identify factors associated with outpatient contacts at community mental health services of patients with schizophrenia or related disorders. METHODS This cross-sectional study analyzed 1097 patients. The main outcome measure was the total number of outpatient consultations during one year. Independent variables were related to socio-demographic, clinical and use of service factors. Data were collected from clinical records. RESULTS The multilevel linear regression model explained 46.35% of the variance. Patients with significantly more contacts with ambulatory services were not working and were receiving welfare benefits (p = 0.02), had no formal education (p = 0.02), had a global level of severity of two or three (four being the most severe) (p < 0.001), with one or more inpatient admissions (p < 0.001), and in contact with both types of professional (nurses and psychiatrists) (p < 0.001). The patients with the fewest ambulatory contacts were those with diagnoses of persistent delusional disorders (p = 0.04) and those who were attended by four of the 13 psychiatrists (p < 0.001). CONCLUSIONS As expected, the variables that explained the use of community service could be viewed as proxies for severity of illness. The most surprising finding, however, was that a group of four psychiatrists was also independently associated with use of ambulatory services by patients with schizophrenia or related disorders. More research is needed to carefully examine how professional support networks interact to affect use of mental health.