Determining the genome-wide kinship coefficient seems unhelpful in distinguishing consanguineous couples with a high versus low risk for adverse reproductive outcome

Background: Offspring of consanguineous couples are at increased risk of congenital disorders. The risk increases as parents are more closely related. Individuals that have the same degree of relatedness according to their pedigree, show variable genomic kinship coefficients. To investigate whether we can differentiate between couples with high- and low risk for offspring with congenital disorders, we have compared the genomic kinship coefficient of consanguineous parents with a child affected with an autosomal recessive disorder with that of consanguineous parents with only healthy children, corrected for the degree of pedigree relatedness. Methods: 151 consanguineous couples (73 cases and 78 controls) from 10 different ethnic backgrounds were genotyped on the Affymetrix platform and passed quality control checks. After pruning SNPs in linkage disequilibrium, 57,358 SNPs remained. Kinship coefficients were calculated using three different toolsets: PLINK, King and IBDelphi, yielding five different estimates (IBDelphi, PLINK (all), PLINK (by population), King robust (all) and King homo (by population)). We performed a one-sided Mann Whitney test to investigate whether the median relative difference regarding observed and expected kinship coefficients is bigger for cases than for controls. Furthermore, we fitted a mixed effects linear model to correct for a possible population effect. Results: Although the estimated degrees of genomic relatedness with the different toolsets show substantial variability, correlation measures between the different estimators demonstrated moderate to strong correlations. Controls have higher point estimates for genomic kinship coefficients. The one-sided Mann Whitney test did not show any evidence for a higher median relative difference for cases compared to controls. Neither did the regression analysis exhibit a positive association between case–control status and genomic kinship coefficient. Conclusions: In this case–control setting, in which we compared consanguineous couples corrected for degree of pedigree relatedness, a higher degree of genomic relatedness was not significantly associated with a higher likelihood of having an affected child. Further translational research should focus on which parts of the genome and which pathogenic mutations couples are sharing. Looking at relatedness coefficients by determining genome-wide SNPs does not seem to be an effective measure for prospective risk assessment in consanguineous parents

Comprehensive global genome dynamics of Chlamydia trachomatis show ancient diversification followed by contemporary mixing and recent lineage expansion.

Chlamydia trachomatis is the world's most prevalent bacterial sexually transmitted infection and leading infectious cause of blindness, yet it is one of the least understood human pathogens, in part due to the difficulties of in vitro culturing and the lack of available tools for genetic manipulation. Genome sequencing has reinvigorated this field, shedding light on the contemporary history of this pathogen. Here, we analyze 563 full genomes, 455 of which are novel, to show that the history of the species comprises two phases, and conclude that the currently circulating lineages are the result of evolution in different genomic ecotypes. Temporal analysis indicates these lineages have recently expanded in the space of thousands of years, rather than the millions of years as previously thought, a finding that dramatically changes our understanding of this pathogen's history. Finally, at a time when almost every pathogen is becoming increasingly resistant to antimicrobials, we show that there is no evidence of circulating genomic resistance in C. trachomatis

Evaluation of sexual history-based screening of anatomic sites for chlamydia trachomatis and neisseria gonorrhoeae infection in men having sex with men in routine practice

<p>Abstract</p> <p>Background</p> <p>Sexually transmitted infection (STI) screening programmes are implemented in many countries to decrease burden of STI and to improve sexual health. Screening for <it>Chlamydia trachomatis </it>and <it>Neisseria gonorrhoeae </it>has a prominent role in these protocols. Most of the screening programmes concerning men having sex with men (MSM) are based on opportunistic urethral testing. In The Netherlands, a history-based approach is used. The aim of this study is to evaluate the protocol of screening anatomic sites for <it>C. trachomatis </it>and <it>N. gonorrhoeae </it>infection based on sexual history in MSM in routine practice in The Netherlands.</p> <p>Methods</p> <p>All MSM visiting the clinic for STI in The Hague are routinely asked about their sexual practice during consulting. As per protocol, tests for urogenital, oropharyngeal and anorectal infection are obtained based on reported site(s) of sexual contact. All consultations are entered into a database as part of the national STI monitoring system. Data of an 18 months period were retrieved from this database and analysed.</p> <p>Results</p> <p>A total of 1455 consultations in MSM were registered during the study period. The prevalence of <it>C. trachomatis </it>and <it>N. gonorrhoeae </it>per anatomic site was: urethral infection 4.0% respectively and 2.8%, oropharynx 1.5% and 4.2%, and anorectum 8.2% and 6.0%. The majority of chlamydia cases (72%) involved a single anatomic site, which was especially manifest for anorectal infections (79%), while 42% of gonorrhoea cases were single site. Twenty-six percent of MSM with anorectal chlamydia and 17% with anorectal gonorrhoea reported symptoms of proctitis; none of the oropharyngeal infections were symptomatic. Most cases of anorectal infection (83%) and oropharyngeal infection (100%) would have remained undiagnosed with a symptom-based protocol.</p> <p>Conclusions</p> <p>The current strategy of sexual-history based screening of multiple anatomic sites for chlamydia and gonorrhoea in MSM is a useful and valid guideline which is to be preferred over a symptom-based screening protocol.</p

The CD14 functional gene polymorphism -260 C>T is not involved in either the susceptibility to Chlamydia trachomatis infection or the development of tubal pathology

BACKGROUND: The functional polymorphism -260 C>T in the LPS sensing TLR4 co-receptor CD14 gene enhances the transcriptional activity and results in a higher CD14 receptor density. Individuals carrying the T/T genotype also have significantly higher serum levels of soluble CD14. The T allele of this polymorphism has recently been linked to Chlamydia pneumoniae infection. We investigated the role of the CD14 -260 C>T polymorphism in the susceptibility to and severity (defined as subfertility and/or tubal pathology) of C. trachomatis infection in Dutch Caucasian women. METHODS: The different CD14 -260 C>T genotypes were assessed by PCR-based RFLP analysis in three cohorts: 1) A cohort (n = 576) of women attending a STD clinic, 2) a cohort (n = 253) of women with subfertility, and 3) an ethnically matched control cohort (n = 170). The following variables were used in the analysis: In cohort 1 the CT-DNA status, CT IgG serology status, self-reported symptoms and in cohort 2, the CT IgG serology status and the tubal status at laparoscopy. RESULTS: In the control cohort the CC, CT and TT genotype distribution was: 28.2%, 48.2%, and 23.5% respectively. No differences were found in the overall prevalence of CD14 -260 genotypes (28.1%, 50.7%, and 21.2%) in cohort 1 when compared to the control cohort. Also no differences were observed in women with or without CT-DNA, with or without serological CT responses, with or without symptoms, or in combinations of these three variables. In subfertile women with tubal pathology (cohort 2, n = 50) the genotype distribution was 28.0%, 48.0%, and 24.0% and in subfertile women without tubal pathology (n = 203), 27.6%, 49.3% and 23.2%. The genotype distribution was unchanged when CT IgG status was introduced in the analyses. CONCLUSION: The CD14 -260 C>T genotype distributions were identical in all three cohorts, showing that this polymorphism is not involved in the susceptibility to or severity of sequelae of C. trachomatis infection

Interruption of CXCL13-CXCR5 Axis Increases Upper Genital Tract Pathology and Activation of NKT Cells following Chlamydial Genital Infection

Peer reviewe

Bayesian Poisson log-bilinear models for mortality projections with multiple populations

Life insurers, pension funds, health care providers and social security institutions face increasing expenses due to continuing improvements of mortality rates. The actuarial and demographic literature has introduced a myriad of (deterministic and stochastic) models to forecast mortality rates of single populations. This paper presents a Bayesian analysis of two related multi-population mortality models of log-bilinear type, designed for two or more populations. Using a larger set of data, multi-population mortality models allow joint modelling and projection of mortality rates by identifying characteristics shared by all sub-populations as well as sub-population specific effects on mortality. This is important when modeling and forecasting mortality of males and females, regions within a country and when dealing with index-based longevity hedges. Our first model is inspired by the two factor Lee-Carter model of Renshaw and Haberman (Insur Math Eco 33(2):255-272, 2003) and the common factor model of Carter and Lee (Int J forecast 8:393-411, 1992. The second model is the augmented common factor model of Li and Lee (Demography 42(3):575-594, 2005). This paper approaches both models in a statistical way, using a Poisson distribution for the number of deaths at a certain age and in a certain time period. Moreover, we use Bayesian statistics to calibrate the models and to produce mortality forecasts. We develop the technicalities necessary for Markov Chain Monte Carlo ([MCMC]) simulations and provide software implementation (in R) for the models discussed in the paper. Key benefits of this approach are multiple. We jointly calibrate the Poisson likelihood for the number of deaths and the times series models imposed on the time dependent parameters, we enable full allowance for parameter uncertainty and we are able to handle missing data as well as small sample populations. We compare and contrast results from both models to the results obtained with a frequentist single population approach and a least squares estimation of the augmented common factor model