Orosomucoid (alpha1-acid glycoprotein) plasma concentration and genetic variants: effects on human immunodeficiency virus protease inhibitor clearance and cellular accumulation

BACKGROUND AND OBJECTIVE: Protease inhibitors are highly bound to orosomucoid (ORM) (alpha1-acid glycoprotein), an acute-phase plasma protein encoded by 2 polymorphic genes, which may modulate their disposition. Our objective was to determine the influence of ORM concentration and phenotype on indinavir, lopinavir, and nelfinavir apparent clearance (CL(app)) and cellular accumulation. Efavirenz, mainly bound to albumin, was included as a control drug. METHODS: Plasma and cells samples were collected from 434 human immunodeficiency virus-infected patients. Total plasma and cellular drug concentrations and ORM concentrations and phenotypes were determined. RESULTS: Indinavir CL(app) was strongly influenced by ORM concentration (n = 36) (r2 = 0.47 [P = .00004]), particularly in the presence of ritonavir (r2 = 0.54 [P = .004]). Lopinavir CL(app) was weakly influenced by ORM concentration (n = 81) (r2 = 0.18 [P = .0001]). For both drugs, the ORM1 S variant concentration mainly explained this influence (r2 = 0.55 [P = .00004] and r2 = 0.23 [P = .0002], respectively). Indinavir CL(app) was significantly higher in F1F1 individuals than in F1S and SS patients (41.3, 23.4, and 10.3 L/h [P = .0004] without ritonavir and 21.1, 13.2, and 10.1 L/h [P = .05] with ritonavir, respectively). Lopinavir cellular exposure was not influenced by ORM abundance and phenotype. Finally, ORM concentration or phenotype did not influence nelfinavir (n = 153) or efavirenz (n = 198) pharmacokinetics. CONCLUSION: ORM concentration and phenotype modulate indinavir pharmacokinetics and, to a lesser extent, lopinavir pharmacokinetics but without influencing their cellular exposure. This confounding influence of ORM should be taken into account for appropriate interpretation of therapeutic drug monitoring results. Further studies are needed to investigate whether the measure of unbound drug plasma concentration gives more meaningful information than total drug concentration for indinavir and lopinavir.

Progression of pulmonary hyperinflation and trapped gas associated with genetic and environmental factors in children with cystic fibrosis

BACKGROUND: Functional deterioration in cystic fibrosis (CF) may be reflected by increasing bronchial obstruction and, as recently shown, by ventilation inhomogeneities. This study investigated which physiological factors (airway obstruction, ventilation inhomogeneities, pulmonary hyperinflation, development of trapped gas) best express the decline in lung function, and what role specific CFTR genotypes and different types of bronchial infection may have upon this process. METHODS: Serial annual lung function tests, performed in 152 children (77 males; 75 females) with CF (age range: 6-18 y) provided data pertaining to functional residual capacity (FRCpleth, FRCMBNW), volume of trapped gas (VTG), effective specific airway resistance (sReff), lung clearance index (LCI), and forced expiratory indices (FVC, FEV1, FEF50). RESULTS: All lung function parameters showed progression with age. Pulmonary hyperinflation (FRCpleth > 2SDS) was already present in 39% of patients at age 6-8 yrs, increasing to 67% at age 18 yrs. The proportion of patients with VTG > 2SDS increased from 15% to 54% during this period. Children with severe pulmonary hyperinflation and trapped gas at age 6-8 yrs showed the most pronounced disease progression over time. Age related tracking of lung function parameters commences early in life, and is significantly influenced by specific CFTR genotypes. The group with chronic P. aeruginosa infection demonstrated most rapid progression in all lung function parameters, whilst those with chronic S. aureus infection had the slowest rate of progression. LCI, measured as an index of ventilation inhomogeneities was the most sensitive discriminator between the 3 types of infection examined (p < 0.0001). CONCLUSION: The relationships between lung function indices, CFTR genotypes and infective organisms observed in this study suggest that measurement of other lung function parameters, in addition to spirometry alone, may provide important information about disease progression in CF.

A Fully Bayesian Approach for Combining Multilevel Failure Information in Fault Tree Quantification and Corresponding Optimal Resource Allocation

This paper presents a fully Bayesian approach that simultaneously combines basic event and statistically independent higher event-level failure data in fault tree quantification. Such higher-level data could correspond to train, sub-system or system failure events. The full Bayesian approach also allows the highest-level data that are usually available for existing facilities to be automatically propagated to lower levels. A simple example illustrates the proposed approach. The optimal allocation of resources for collecting additional data from a choice of different level events is also presented. The optimization is achieved using a genetic algorithm.

Distribution and genetic variability among Campylobacter spp. isolates from different animal species and humans in Switzerland

In Switzerland, a national database with 1028 Campylobacter isolates from poultry, pigs, cats, dogs, cattle, humans, zoo animals and water has been created. The database contains the genetic fingerprint and background information of each Campylobacter isolate. Dominant species could be identified in the different sources with a majority of Campylobacter jejuni in poultry (73%), humans (79%), cattle (95%), zoo animals (40%) and water (100%), of Campylobacter coli in pigs (72%), and of Campylobacter upsaliensis/helveticus in cats and dogs (55%). The comparison of three genotyping methods, amplified fragment length polymorphism (AFLP), pulsed field gel electrophoresis and restriction fragment length polymorphism, revealed that AFLP allows discrimination between the different Campylobacter species and is the most appropriate method to distinguish specific strains within the same species. Genotyping analysis demonstrated that the Campylobacter population is heterogeneous among the different sources and that no dominant clone is spread in the country. Genotyping and the resulting database are useful tools to trace back future Campylobacter infections.

Genetic association studies under the population stratification, family pedigree and application to genome-wide association studies

This dissertation has three separate parts: the first part deals with the general pedigree association testing incorporating continuous covariates; the second part deals with the association tests under population stratification using the conditional likelihood tests; the third part deals with the genome-wide association studies based on the real rheumatoid arthritis (RA) disease data sets from Genetic Analysis Workshop 16 (GAW16) problem 1. Many statistical tests are developed to test the linkage and association using either case-control status or phenotype covariates for family data structure, separately. Those univariate analyses might not use all the information coming from the family members in practical studies. On the other hand, the human complex disease do not have a clear inheritance pattern, there might exist the gene interactions or act independently. In part I, the new proposed approach MPDT is focused on how to use both the case control information as well as the phenotype covariates. This approach can be applied to detect multiple marker effects. Based on the two existing popular statistics in family studies for case-control and quantitative traits respectively, the new approach could be used in the simple family structure data set as well as general pedigree structure. The combined statistics are calculated using the two statistics; A permutation procedure is applied for assessing the p-value with adjustment from the Bonferroni for the multiple markers. We use simulation studies to evaluate the type I error rates and the powers of the proposed approach. Our results show that the combined test using both case-control information and phenotype covariates not only has the correct type I error rates but also is more powerful than the other existing methods. For multiple marker interactions, our proposed method is also very powerful. Selective genotyping is an economical strategy in detecting and mapping quantitative trait loci in the genetic dissection of complex disease. When the samples arise from different ethnic groups or an admixture population, all the existing selective genotyping methods may result in spurious association due to different ancestry distributions. The problem can be more serious when the sample size is large, a general requirement to obtain sufficient power to detect modest genetic effects for most complex traits. In part II, I describe a useful strategy in selective genotyping while population stratification is present. Our procedure used a principal component based approach to eliminate any effect of population stratification. The paper evaluates the performance of our procedure using both simulated data from an early study data sets and also the HapMap data sets in a variety of population admixture models generated from empirical data. There are one binary trait and two continuous traits in the rheumatoid arthritis dataset of Problem 1 in the Genetic Analysis Workshop 16 (GAW16): RA status, AntiCCP and IgM. To allow multiple traits, we suggest a set of SNP-level F statistics by the concept of multiple-correlation to measure the genetic association between multiple trait values and SNP-specific genotypic scores and obtain their null distributions. Hereby, we perform 6 genome-wide association analyses using the novel one- and two-stage approaches which are based on single, double and triple traits. Incorporating all these 6 analyses, we successfully validate the SNPs which have been identified to be responsible for rheumatoid arthritis in the literature and detect more disease susceptibility SNPs for follow-up studies in the future. Except for chromosome 13 and 18, each of the others is found to harbour susceptible genetic regions for rheumatoid arthritis or related diseases, i.e., lupus erythematosus. This topic is discussed in part III.

STrengthening the REporting of Genetic Association studies (STREGA)--an extension of the STROBE statement

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the STrengthening the Reporting of OBservational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modelling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed, but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct or analysis.

STrengthening the REporting of Genetic Association Studies (STREGA)--an extension of the STROBE statement

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the STrengthening the Reporting of OBservational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modelling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

Strengthening the reporting of genetic association studies (STREGA): an extension of the strengthening the reporting of observational studies in epidemiology (STROBE) statement

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence, the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association (STREGA) studies initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed, but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

STrengthening the REporting of Genetic Association Studies (STREGA): an extension of the STROBE statement

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modelling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

STrengthening the REporting of Genetic Association studies (STREGA): an extension of the STROBE Statement

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information into the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the STrengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and issues of data volume that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

Strengthening the reporting of genetic association studies (STREGA): an extension of the STROBE statement

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

Strengthening the reporting of genetic association studies (STREGA): an extension of the STROBE Statement

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

Phylogeny and prediction of genetic similarity of Cronobacter and related taxa by multilocus sequence analysis (MLSA)

Multilocus sequence analysis (MLSA) based on recN, rpoA and thdF genes was done on more than 30 species of the family Enterobacteriaceae with a focus on Cronobacter and the related genus Enterobacter. The sequences provide valuable data for phylogenetic, taxonomic and diagnostic purposes. Phylogenetic analysis showed that the genus Cronobacter forms a homogenous cluster related to recently described species of Enterobacter, but distant to other species of this genus. Combining sequence information on all three genes is highly representative for the species' %GC-content used as taxonomic marker. Sequence similarity of the three genes and even of recN alone can be used to extrapolate genetic similarities between species of Enterobacteriaceae. Finally, the rpoA gene sequence, which is the easiest one to determine, provides a powerful diagnostic tool to identify and differentiate species of this family. The comparative analysis gives important insights into the phylogeny and genetic relatedness of the family Enterobacteriaceae and will serve as a basis for further studies and clarifications on the taxonomy of this large and heterogeneous family.

Genetic diversity and ecological success of Staphylococcus aureus strains colonizing humans

The genetic determinants and phenotypic traits which make a Staphylococcus aureus strain a successful colonizer are largely unknown. The genetic diversity and population structure of 133 S. aureus isolates from healthy, generally risk-free adult carriers were investigated using four different typing methods: multilocus sequence typing (MLST), amplified fragment length polymorphism analysis (AFLP), double-locus sequence typing (DLST), and spa typing were compared. Carriage isolates displayed great genetic diversity which could only be revealed fully by DLST. Results of AFLP and MLST were highly concordant in the delineation of genotypic clusters of closely related isolates, roughly equivalent to clonal complexes. spa typing and DLST provided considerably less phylogenetic information. The resolution of spa typing was similar to that of AFLP and inferior to that of DLST. AFLP proved to be the most universal method, combining a phylogeny-building capacity similar to that of MLST with a much higher resolution. However, it had a lower reproducibility than sequencing-based MLST, DLST, and spa typing. We found two cases of methicillin-resistant S. aureus colonization, both of which were most likely associated with employment at a health service. Of 21 genotypic clusters detected, 2 were most prevalent: cluster 45 and cluster 30 each colonized 24% of the carrier population. The number of bacteria found in nasal samples varied significantly among the clusters, but the most prevalent clusters were not particularly numerous in the nasal samples. We did not find much evidence that genotypic clusters were associated with different carrier characteristics, such as age, sex, medical conditions, or antibiotic use. This may provide empirical support for the idea that genetic clusters in bacteria are maintained in the absence of adaptation to different niches. Alternatively, carrier characteristics other than those evaluated here or factors other than human hosts may exert selective pressure maintaining genotypic clusters.

Multiplex strategy for multilocus sequence typing, fla typing, and genetic determination of antimicrobial resistance of Campylobacter jejuni and Campylobacter coli isolates collected in Switzerland

We present an optimized multilocus sequence typing (MLST) scheme with universal primer sets for amplifying and sequencing the seven target genes of Campylobacter jejuni and Campylobacter coli. Typing was expanded by sequence determination of the genes flaA and flaB using optimized primer sets. This approach is compatible with the MLST and flaA schemes used in the PubMLST database and results in an additional typing method using the flaB gene sequence. An identification module based on the 16S rRNA and rpoB genes was included, as well as the genetic determination of macrolide and quinolone resistances based on mutations in the 23S rRNA and gyrA genes. Experimental procedures were simplified by multiplex PCR of the 13 target genes. This comprehensive approach was evaluated with C. jejuni and C. coli isolates collected in Switzerland. MLST of 329 strains resulted in 72 sequence types (STs) among the 186 C. jejuni strains and 39 STs for the 143 C. coli isolates. Fourteen (19%) of the C. jejuni and 20 (51%) of the C. coli STs had not been found previously. In total, 35% of the C. coli strains collected in Switzerland contained mutations conferring antibiotic resistance only to quinolone, 15% contained mutations conferring resistance only to macrolides, and 6% contained mutations conferring resistance to both classes of antibiotics. In C. jejuni, these values were 31% and 0% for quinolone and macrolide resistance, respectively. The rpoB sequence allowed phylogenetic differentiation between C. coli and C. jejuni, which was not possible by 16S rRNA gene analysis. An online Integrated Database Network System (SmartGene, Zug, Switzerland)-based platform for MLST data analysis specific to Campylobacter was implemented. This Web-based platform allowed automated allele and ST designation, as well as epidemiological analysis of data, thus streamlining and facilitating the analysis workflow. Data networking facilitates the exchange of information between collaborating centers. The described approach simplifies and improves the genotyping of Campylobacter, allowing cost- and time-efficient routine monitoring.