11 research outputs found

    Advancing the public health applications of Chlamydia trachomatis serology.

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    Genital Chlamydia trachomatis infection is the most commonly diagnosed sexually transmitted infection. Trachoma is caused by ocular infection with C trachomatis and is the leading infectious cause of blindness worldwide. New serological assays for C trachomatis could facilitate improved understanding of C trachomatis epidemiology and prevention. C trachomatis serology offers a means of investigating the incidence of chlamydia infection and might be developed as a biomarker of scarring sequelae, such as pelvic inflammatory disease. Therefore, serological assays have potential as epidemiological tools to quantify unmet need, inform service planning, evaluate interventions including screening and treatment, and to assess new vaccine candidates. However, questions about the performance characteristics and interpretation of C trachomatis serological assays remain, which must be addressed to advance development within this field. In this Personal View, we explore the available information about C trachomatis serology and propose several priority actions. These actions involve development of target product profiles to guide assay selection and assessment across multiple applications and populations, establishment of a serum bank to facilitate assay development and evaluation, and development of technical and statistical methods for assay evaluation and analysis of serological findings. The field of C trachomatis serology will benefit from collaboration across the public health community to align technological developments with their potential applications

    Minimal information for studies of extracellular vesicles (MISEV2023): From basic to advanced approaches

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    Extracellular vesicles (EVs), through their complex cargo, can reflect the state of their cell of origin and change the functions and phenotypes of other cells. These features indicate strong biomarker and therapeutic potential and have generated broad interest, as evidenced by the steady year-on-year increase in the numbers of scientific publications about EVs. Important advances have been made in EV metrology and in understanding and applying EV biology. However, hurdles remain to realising the potential of EVs in domains ranging from basic biology to clinical applications due to challenges in EV nomenclature, separation from non-vesicular extracellular particles, characterisation and functional studies. To address the challenges and opportunities in this rapidly evolving field, the International Society for Extracellular Vesicles (ISEV) updates its 'Minimal Information for Studies of Extracellular Vesicles', which was first published in 2014 and then in 2018 as MISEV2014 and MISEV2018, respectively. The goal of the current document, MISEV2023, is to provide researchers with an updated snapshot of available approaches and their advantages and limitations for production, separation and characterisation of EVs from multiple sources, including cell culture, body fluids and solid tissues. In addition to presenting the latest state of the art in basic principles of EV research, this document also covers advanced techniques and approaches that are currently expanding the boundaries of the field. MISEV2023 also includes new sections on EV release and uptake and a brief discussion of in vivo approaches to study EVs. Compiling feedback from ISEV expert task forces and more than 1000 researchers, this document conveys the current state of EV research to facilitate robust scientific discoveries and move the field forward even more rapidly

    A Machine Learning-Based Analytic Pipeline Applied to Clinical and Serum IgG Immunoproteome Data To Predict Chlamydia trachomatis Genital Tract Ascension and Incident Infection in Women

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    ABSTRACT We developed a reusable and open-source machine learning (ML) pipeline that can provide an analytical framework for rigorous biomarker discovery. We implemented the ML pipeline to determine the predictive potential of clinical and immunoproteome antibody data for outcomes associated with Chlamydia trachomatis (Ct) infection collected from 222 cis-gender females with high Ct exposure. We compared the predictive performance of 4 ML algorithms (naive Bayes, random forest, extreme gradient boosting with linear booster [xgbLinear], and k-nearest neighbors [KNN]), screened from 215 ML methods, in combination with two different feature selection strategies, Boruta and recursive feature elimination. Recursive feature elimination performed better than Boruta in this study. In prediction of Ct ascending infection, naive Bayes yielded a slightly higher median value of are under the receiver operating characteristic curve (AUROC) 0.57 (95% confidence interval [CI], 0.54 to 0.59) than other methods and provided biological interpretability. For prediction of incident infection among women uninfected at enrollment, KNN performed slightly better than other algorithms, with a median AUROC of 0.61 (95% CI, 0.49 to 0.70). In contrast, xgbLinear and random forest had higher predictive performances, with median AUROC of 0.63 (95% CI, 0.58 to 0.67) and 0.62 (95% CI, 0.58 to 0.64), respectively, for women infected at enrollment. Our findings suggest that clinical factors and serum anti-Ct protein IgGs are inadequate biomarkers for ascension or incident Ct infection. Nevertheless, our analysis highlights the utility of a pipeline that searches for biomarkers and evaluates prediction performance and interpretability. IMPORTANCE Biomarker discovery to aid early diagnosis and treatment using machine learning (ML) approaches is a rapidly developing area in host-microbe studies. However, lack of reproducibility and interpretability of ML-driven biomarker analysis hinders selection of robust biomarkers that can be applied in clinical practice. We thus developed a rigorous ML analytical framework and provide recommendations for enhancing reproducibility of biomarkers. We emphasize the importance of robustness in selection of ML methods, evaluation of performance, and interpretability of biomarkers. Our ML pipeline is reusable and open-source and can be used not only to identify host-pathogen interaction biomarkers but also in microbiome studies and ecological and environmental microbiology research

    Whole-Proteome Microarray Analysis of The Netherlands Chlamydia Cohort Study.

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    Chlamydia trachomatis (Ct) whole-proteome microarrays were utilized to identify antibody patterns associated with infection; pelvic inflammatory disease (PID), tubal factor infertility, chronic pelvic pain (CPP) and ectopic pregnancy in a subsample of the Netherlands Chlamydia cohort study. Serum pools were analyzed on whole-proteome arrays. The 121 most reactive antigens identified during whole-proteome arrays were selected for further analysis with minimized microarrays that allowed for single sera analysis. From the 232 single sera; 145 (62.5%) serum samples were reactive for at least one antigen. To discriminate between positive and negative serum samples; we created a panel of in total 18 antigens which identified 96% of all microarray positive samples. Antigens CT_858; CT_813 and CT_142 were most reactive. Comparison of antibody reactivity's among women with and without Ct related sequelae revealed that the reactivity of CT_813 and CT_142 was less common among women with PID compared to women without (29.0% versus 58.6%, p = 0.005 and 25.8% versus 50.6%, p = 0.017 respectively). CT_858 was less common among CPP cases compared to controls (33.3% versus 58.6; p = 0.028). Using a whole-proteome array to select antigens for minimized arrays allows for the identification of novel informative antigens as general infection markers or disease associated antigens

    Novel Autoantibody Signatures in Sera of Patients with Pancreatic Cancer, Chronic Pancreatitis and Autoimmune Pancreatitis: A Protein Microarray Profiling Approach

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    Identification of disease-associated autoantibodies is of high importance. Their assessment could complement current diagnostic modalities and assist the clinical management of patients. We aimed at developing and validating high-throughput protein microarrays able to screen patients' sera to determine disease-specific autoantibody-signatures for pancreatic cancer (PDAC), chronic pancreatitis (CP), autoimmune pancreatitis and their subtypes (AIP-1 and AIP-2). In-house manufactured microarrays were used for autoantibody-profiling of IgG-enriched preoperative sera from PDAC-, CP-, AIP-1-, AIP-2-, other gastrointestinal disease (GID) patients and healthy controls. As a top-down strategy, three different fluorescence detection-based protein-microarrays were used: large with 6400, intermediate with 345, and small with 36 full-length human recombinant proteins. Large-scale analysis revealed 89 PDAC, 98 CP and 104 AIP immunogenic antigens. Narrowing the selection to 29 autoantigens using pooled sera first and individual sera afterwards allowed a discrimination of CP and AIP from PDAC. For validation, predictive models based on the identified antigens were generated which enabled discrimination between PDAC and AIP-1 or AIP-2 yielded high AUC values of 0.940 and 0.925, respectively. A new repertoire of autoantigens was identified and their assembly as a multiplex test will provide a fast and cost-effective tool for differential diagnosis of pancreatic diseases with high clinical relevance

    Differences in Chlamydia trachomatis seroprevalence between ethnic groups cannot be fully explained by socioeconomic status, sexual healthcare seeking behavior or sexual risk behavior: a cross-sectional analysis in the HEalthy LIfe in an Urban Setting (HELIUS) study

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    Abstract Background In the Netherlands, there are strong disparities in Chlamydia trachomatis (CT) prevalence between ethnic groups. The current study aims to identify whether socioeconomic status, sexual risk behavior and sexual healthcare seeking behavior may explain differences in CT seroprevalence between ethnic groups. Methods We used 2011–2014 baseline data of the HELIUS (HEalthy LIfe in an Urban Setting) study, a multi-ethnic population-based cohort study in Amsterdam, the Netherlands, including participants from Dutch, African Surinamese, South-Asian Surinamese, Ghanaian, Moroccan and Turkish origin. For this analysis, we selected sexually active, heterosexual participants aged 18–34 years old. CT seroprevalence was determined using a multiplex serology assay. The CT seroprevalence ratios between different ethnicities are calculated and adjusted for potential indicators of socioeconomic status, sexual risk behavior and sexual healthcare seeking behavior. Results The study population consisted of 2001 individuals (52.8% female) with a median age of 28 years (IQR 24–31). CT seropositivity differed by ethnicities and ranged from 71.6% (African Surinamese), and 67.9% (Ghanaian) to 31.1% (Turkish). The CT seroprevalence ratio of African Surinamese was 1.72 (95% CI 1.43–2.06) and 1.52 (95% CI 1.16–1.99) of Ghanaian as compared to the Dutch reference group, after adjustment for socioeconomic status, sexual risk behavior and sexual healthcare seeking behavior. Conclusions Indicators of socioeconomic status, sexual risk behavior, and sexual health seeking behavior could not explain the higher CT seroprevalence among African Surinamese and Ghanaian residents of Amsterdam

    Antibodies against chlamydia trachomatis and ovarian cancer risk in two independent populations

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    Background: Pelvic inflammatory disease (PID) has been associated with ovarian cancer risk. To clarify the role of Chlamydia trachomatis and other infectious agents in the development of ovarian cancer, we evaluated the association of serologic markers with incident ovarian cancer using a staged approach in two independent populations. Methods: Studies included: 1) a case-control study in Poland (244 ovarian cancers/556 control subjects) and 2) a prospective nested case-control study in the PLCO Cancer Screening Trial (160 ovarian cancers/159 control subjects). Associations of serologic marker levels with ovarian cancer risk at diagnostic as well as higher thresholds, identified in Poland and independently evaluated in PLCO, were estimated using multivariable adjusted logistic regression. Results: In the Polish study, antibodies (based on laboratory cut-point) against the chlamydia plasmid-encoded Pgp3 protein (serological gold standard) were associated with increased ovarian cancer risk (adjusted odds ratio [OR] = 1.63, 95% confidence interval [CI] = 1.20 to 2.22); when a positive result was redefined at higher levels, ovarian cancer risk was increased (cut-point 2: OR = 2.00, 95% CI = 1.38 to 2.89; cut-point 3 [max OR]: OR = 2.19, 95% CI = 1.29 to 3.73). In the prospective PLCO study, Pgp3 antibodies were associated with elevated risk at the laboratory cut-point (OR = 1.43, 95% CI = 0.78 to 2.63) and more stringent cut-points (cut-point 2: OR = 2.25, 95% CI = 1.07 to 4.71); cut-point 3: OR = 2.53, 95% CI = 0.63 to 10.08). In both studies, antibodies against other infectious agents measured were not associated with risk. Conclusions: In two independent populations, antibodies against prior/current C. trachomatis (Pgp3) were associated with a doubling in ovarian cancer risk, whereas markers of other infectious agents were unrelated. These findings lend support for an association between PID and ovarian cancer

    Advancing the public health applications of Chlamydia trachomatis serology

    No full text
    Genital Chlamydia trachomatis infection is the most commonly diagnosed sexually transmitted infection. Trachoma is caused by ocular infection with C trachomatis and is the leading infectious cause of blindness worldwide. New serological assays for C trachomatis could facilitate improved understanding of C trachomatis epidemiology and prevention. C trachomatis serology offers a means of investigating the incidence of chlamydia infection and might be developed as a biomarker of scarring sequelae, such as pelvic inflammatory disease. Therefore, serological assays have potential as epidemiological tools to quantify unmet need, inform service planning, evaluate interventions including screening and treatment, and to assess new vaccine candidates. However, questions about the performance characteristics and interpretation of C trachomatis serological assays remain, which must be addressed to advance development within this field. In this Personal View, we explore the available information about C trachomatis serology and propose several priority actions. These actions involve development of target product profiles to guide assay selection and assessment across multiple applications and populations, establishment of a serum bank to facilitate assay development and evaluation, and development of technical and statistical methods for assay evaluation and analysis of serological findings. The field of C trachomatis serology will benefit from collaboration across the public health community to align technological developments with their potential applications.</p
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