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.

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 () infection collected from 222 cis-gender females with high exposure. We compared the predictive performance of 4 ML algorithms (naive Bayes, random forest, extreme gradient boosting with linear booster [xgbLinear], and -nearest neighbors [KNN]), screened from 215 ML methods, in combination with two different feature selection strategies, Boruta and recursive feature elimination.

Discovery and systematic assessment of early biomarkers that predict progression to severe COVID-19 disease.

Background: The clinical course of COVID-19 patients ranges from asymptomatic infection, via mild and moderate illness, to severe disease and even fatal outcome. Biomarkers which enable an early prediction of the severity of COVID-19 progression, would be enormously beneficial to guide patient care and early intervention prior to hospitalization.

Methods: Here we describe the identification of plasma protein biomarkers using an antibody microarray-based approach in order to predict a severe cause of a COVID-19 disease already in an early phase of SARS-CoV-2 infection.

Reduced Endometrial Ascension and Enhanced Reinfection Associated With Immunoglobulin G Antibodies to Specific Chlamydia trachomatis Proteins in Women at Risk for Chlamydia.

Background: Previous research revealed antibodies targeting Chlamydia trachomatis elementary bodies was not associated with reduced endometrial or incident infection in C. trachomatis-exposed women. However, data on the role of C.

Development of Whole-Proteome Arrays and Identification of Serologic Biomarkers for Noncardia Gastric Cancer in the MCC-Spain Study.

Background: () is a bacterial carcinogen and the leading risk factor for noncardia gastric cancer (NCGC). Detecting antibodies against specific proteins in peripheral blood can be applied to characterize infection and determine disease associations. Most studies analyzing the association between infection and gastric cancer have focused on previously identified antigens, predominantly the virulence factor cytotoxin-associated gene A (CagA).

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

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).

Antibodies against human papillomavirus proteins in Barrett's dysplasia and intramucosal esophageal adenocarcinoma.

High-risk human papillomavirus (HPV) types 16/18 have been associated with Barrett's dysplasia (BD)/esophageal adenocarcinoma (EAC). Nevertheless, no data exist in relation to serological analysis for HPV antibodies in BD/EAC with site-specific viral DNA status. We prospectively examined antibodies to multiple HPV types in 438 patients representing hospital/reflux controls and Barrett's metaplasia (BM)/BD/intramucosal EAC.

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

(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.

The transcription factor FLI1 promotes cancer progression by affecting cell cycle regulation.

Binding of transcription factors to mutated DNA sequences is a likely regulator of cancer progression. Noncoding regulatory mutations such as those on the core promoter of the gene encoding human telomerase reverse transcriptase have been shown to affect gene expression in cancer. Using a protein microarray of 667 transcription factor DNA-binding domains and subsequent functional assays, we looked for transcription factors that preferentially bind the mutant hTERT promoter and characterized their downstream effects.

Sexually transmitted infections and risk of epithelial ovarian cancer: results from the Nurses' Health Studies.

Background: Sexually transmitted infections (STIs) are associated with pelvic inflammatory disease and tubal pathologies. Given the tubal origin of a proportion of ovarian cancers, STIs may be relevant in their aetiology.

Methods: Antibodies indicating past infection with Chlamydia trachomatis, Mycoplasma genitalium, herpes simplex virus type 2, and against human papillomavirus oncogenes (L1 and E6+E7 oncoproteins of types 16, 18, 45) were measured in prediagnosis plasma samples in a nested case-control study in the Nurses' Health Studies (n = 337 cases 1:1 matched to controls).

, Cell-free Protein Expression on Microarrays and Their Use for the Detection of Immune Responses.

Until recently, whole-proteome microarrays for comprehensive studies of protein interactions were mostly produced by individual cloning and cellular expression of very many open reading frames, followed by protein isolation and purification as well as array production. To overcome this cumbersome process, we have developed a method to generate microarrays representing entire proteomes by a combination of multiple spotting and on-chip, cell-free protein expression. Here, we describe the protocol for the production of bacterial protein microarrays.

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.

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.

Advancing the public health applications of Chlamydia trachomatis serology.

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.

Antibodies Against Chlamydia trachomatis and Ovarian Cancer Risk in Two Independent Populations.

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).

Immunoprofiling of Chlamydia trachomatis using whole-proteome microarrays generated by on-chip in situ expression.

Using Chlamydia trachomatis (Ct) as a complex model organism, we describe a method to generate bacterial whole-proteome microarrays using cell-free, on-chip protein expression. Expression constructs were generated by two successive PCRs directly from bacterial genomic DNA. Bacterial proteins expressed on microarrays display antigenic epitopes, thereby providing an efficient method for immunoprofiling of patients and allowing de novo identification of disease-related serum antibodies.