A data browsing application for accessing gene and module-level blood transcriptome profiles of healthy pregnant women from high- and low-resource settings.

Transcriptome profiling data, generated via RNA sequencing, are commonly deposited in public repositories. However, these data may not be easily accessible or usable by many researchers. To enhance data reuse, we present well-annotated, partially analyzed data via a user-friendly web application. This project involved transcriptome profiling of blood samples from 15 healthy pregnant women in a low-resource setting, taken at 6 consecutive time points beginning from the first trimester. Additional blood transcriptome profiles were retrieved from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) public repository, representing a cohort of healthy pregnant women from a high-resource setting. We analyzed these datasets using the fixed BloodGen3 module repertoire. We deployed a web application, accessible at https://thejacksonlaboratory.shinyapps.io/BloodGen3_Pregnancy/which displays the module-level analysis results from both original and public pregnancy blood transcriptome datasets. Users can create custom fingerprint grid and heatmap representations via various navigation options, useful for reports and manuscript preparation. The web application serves as a standalone resource for exploring blood transcript abundance changes during pregnancy. Alternatively, users can integrate it with similar applications developed for earlier publications to analyze transcript abundance changes of a given BloodGen3 signature across a range of disease cohorts. Database URL: https://thejacksonlaboratory.shinyapps.io/BloodGen3_Pregnancy/.

Unveiling the dynamics of the breast milk microbiome: impact of lactation stage and gestational age.

BACKGROUND: Breast milk (BM) provides complete nutrition for infants for the first six months of life and is essential for the development of the newborn's immature immune and digestive systems. While BM was conventionally believed to be sterile, recent advanced high throughput technologies have unveiled the presence of diverse microbial communities in BM. These insights into the BM microbiota have mainly originated from uncomplicated pregnancies, possibly not reflecting the circumstances of mothers with pregnancy complications like preterm birth (PTB). METHODS: In this article, we investigated the BM microbial communities in mothers with preterm deliveries (before 37 weeks of gestation). We compared these samples with BM samples from healthy term pregnancies across different lactation stages (colostrum, transitional and mature milk) using 16S rRNA gene sequencing. RESULTS: Our analysis revealed that the microbial communities became increasingly diverse and compositionally distinct as the BM matured. Specifically, mature BM samples were significantly enriched in Veillonella and lactobacillus (Kruskal Wallis; p < 0.001) compared to colostrum. The comparison of term and preterm BM samples showed that the community structure was significantly different between the two groups (Bray Curtis and unweighted unifrac dissimilarity; p < 0.001). Preterm BM samples exhibited increased species richness with significantly higher abundance of Staphylococcus haemolyticus, Propionibacterium acnes, unclassified Corynebacterium species. Whereas term samples were enriched in Staphylococcus epidermidis, unclassified OD1, and unclassified Veillonella among others. CONCLUSION: Our study underscores the significant influence of pregnancy-related complications, such as preterm birth (before 37 weeks of gestation), on the composition and diversity of BM microbiota. Given the established significance of the maternal microbiome in shaping child health outcomes, this investigation paves the way for identifying modifiable factors that could optimize the composition of BM microbiota, thereby promoting maternal and infant health.

Harnessing large language models (LLMs) for candidate gene prioritization and selection.

BACKGROUND: Feature selection is a critical step for translating advances afforded by systems-scale molecular profiling into actionable clinical insights. While data-driven methods are commonly utilized for selecting candidate genes, knowledge-driven methods must contend with the challenge of efficiently sifting through extensive volumes of biomedical information. This work aimed to assess the utility of large language models (LLMs) for knowledge-driven gene prioritization and selection. METHODS: In this proof of concept, we focused on 11 blood transcriptional modules associated with an Erythroid cells signature. We evaluated four leading LLMs across multiple tasks. Next, we established a workflow leveraging LLMs. The steps consisted of: (1) Selecting one of the 11 modules; (2) Identifying functional convergences among constituent genes using the LLMs; (3) Scoring candidate genes across six criteria capturing the gene's biological and clinical relevance; (4) Prioritizing candidate genes and summarizing justifications; (5) Fact-checking justifications and identifying supporting references; (6) Selecting a top candidate gene based on validated scoring justifications; and (7) Factoring in transcriptome profiling data to finalize the selection of the top candidate gene. RESULTS: Of the four LLMs evaluated, OpenAI's GPT-4 and Anthropic's Claude demonstrated the best performance and were chosen for the implementation of the candidate gene prioritization and selection workflow. This workflow was run in parallel for each of the 11 erythroid cell modules by participants in a data mining workshop. Module M9.2 served as an illustrative use case. The 30 candidate genes forming this module were assessed, and the top five scoring genes were identified as BCL2L1, ALAS2, SLC4A1, CA1, and FECH. Researchers carefully fact-checked the summarized scoring justifications, after which the LLMs were prompted to select a top candidate based on this information. GPT-4 initially chose BCL2L1, while Claude selected ALAS2. When transcriptional profiling data from three reference datasets were provided for additional context, GPT-4 revised its initial choice to ALAS2, whereas Claude reaffirmed its original selection for this module. CONCLUSIONS: Taken together, our findings highlight the ability of LLMs to prioritize candidate genes with minimal human intervention. This suggests the potential of this technology to boost productivity, especially for tasks that require leveraging extensive biomedical knowledge.

High-temporal resolution profiling reveals distinct immune trajectories following the first and second doses of COVID-19 mRNA vaccines.

Knowledge of the mechanisms underpinning the development of protective immunity conferred by mRNA vaccines is fragmentary. Here, we investigated responses to coronavirus disease 2019 (COVID-19) mRNA vaccination via high-temporal resolution blood transcriptome profiling. The first vaccine dose elicited modest interferon and adaptive immune responses, which peaked on days 2 and 5, respectively. The second vaccine dose, in contrast, elicited sharp day 1 interferon, inflammation, and erythroid cell responses, followed by a day 5 plasmablast response. Both post-first and post-second dose interferon signatures were associated with the subsequent development of antibody responses. Yet, we observed distinct interferon response patterns after each of the doses that may reflect quantitative or qualitative differences in interferon induction. Distinct interferon response phenotypes were also observed in patients with COVID-19 and were associated with severity and differences in duration of intensive care. Together, this study also highlights the benefits of adopting high-frequency sampling protocols in profiling vaccine-elicited immune responses.

Understanding the Mechanism of Diabetes Mellitus in a LRBA-Deficient Patient.

The scope of this study is to show that DM in a LRBA-deficient patient with a stop codon mutation (c.3999 G > A) was not mediated through autoimmunity. We have evaluated the ability of the proband's T cells to be activated by assessing their CTLA-4 expression. A nonsignificant difference was seen in the CTLA-4 expression on CD3+ T cells compared to the healthy control at basal level and after stimulation with PMA/ionomycin. Blood transcriptomic analysis have shown a remarkable increase in abundance of transcripts related to CD71+ erythroid cells. There were no differences in the expression of modules related to autoimmunity diseases between the proband and pooled healthy controls. In addition, our novel findings show that siRNA knockdown of LRBA in mouse pancreatic ß-cells leads reduced cellular proinsulin, insulin and consequently insulin secretion, without change in cell viability in cultured MIN6 cells.

Transcriptomic profile investigations highlight a putative role for NUDT16 in sepsis.

Sepsis is an aberrant systemic inflammatory response mediated by the acute activation of the innate immune system. Neutrophils are important contributors to the innate immune response that controls the infection, but harbour the risk of collateral tissue damage such as thrombosis and organ dysfunction. A better understanding of the modulations of cellular processes in neutrophils and other blood cells during sepsis is needed and can be initiated via transcriptomic profile investigations. To that point, the growing repertoire of publicly accessible transcriptomic datasets serves as a valuable resource for discovering and/or assessing the robustness of biomarkers. We employed systematic literature mining, reductionist approach to gene expression profile and empirical in vitro work to highlight the role of a Nudix hydrolase family member, NUDT16, in sepsis. The relevance and implication of the expression of NUDT16 under septic conditions and the putative functional roles of this enzyme are discussed.

When Mosquito HV bites Biomark HD: An automated workflow for high-throughput qPCR.

Automation solutions can significantly improve sample processing efficiency and can be of particular help in core facility settings. Centralized core facilities are being established world-wide aimed at strengthening institutions' clinical and research enterprises and at addressing the need to process large volumes of samples on expensive cutting-edge technologies in a limited time. High-throughput qPCR profiling is a service offered by most genomics facilities. Several platforms have been developed to process large numbers of samples in a short time, including the Fluidigm Biomark HD, which has also been proved useful to increase the SARS-CoV-2 testing capacities. Several automation systems are currently available to miniaturize volumes and improve bioanalytical workflows, including the SPT Labtech Mosquito HV system. Here we have applied the Mosquito HV platform for the automation of the sample preparation of the Fluidigm gene expression workflow. We have successfully automated the pre-amplification and exonuclease cleanup steps with the aim of reducing manual error and sample processing time. We show consistency in the expression of reference genes when assessing pooled RNA control samples for the manual and automated workflows of Fluidigm gene expression profiling.

Risk factor-based screening compared to universal screening for gestational diabetes mellitus in marginalized Burman and Karen populations on the Thailand-Myanmar border: An observational cohort.

Background: Gestational diabetes mellitus (GDM) contributes to maternal and neonatal morbidity. As data from marginalized populations remains scarce, this study compares risk-factor-based to universal GDM screening in a low resource setting. Methods: This is a secondary analysis of data from a prospective preterm birth cohort. Pregnant women were enrolled in the first trimester and completed a 75g oral glucose tolerance test (OGTT) at 24-32 weeks' gestation. To define GDM cases, Hyperglycaemia and Adverse Pregnancy Outcomes (HAPO trial) criteria were used. All GDM positive cases were treated. Sensitivity and specificity of risk-factor-based selection for screening (criteria: age ≥30y, obesity (Body mass index (BMI) ≥27.5kg/m 2), previous GDM, 1 st degree relative with diabetes, previous macrosomia (≥4kg), previous stillbirth, or symphysis-fundal height ≥90th percentile) was compared to universal screening using the OGTT as the gold standard. Adverse maternal and neonatal outcomes were compared by GDM status. Results: GDM prevalence was 13.4% (50/374) (95% CI: 10.3-17.2). Three quarters of women had at least one risk factor (n=271 women), with 37/50 OGTT positive cases correctly identified: sensitivity 74.0% (59.7-85.4) and specificity 27.8% (3.0-33.0). Burman women (self-identified) accounted for 29.1% of the cohort population, but 38.0% of GDM cases. Percentiles for birthweight (p=0.004), head circumference (p=0.002), and weight-length ratio (p=0.030) were higher in newborns of GDM positive compared with non-GDM mothers. 21.7% (75/346) of newborns in the cohort were small-for-gestational age (≤10 th percentile). In Burman women, overweight/obese BMI was associated with a significantly increased adjusted odds ratio 5.03 (95% CI: 1.43-17.64) for GDM compared with normal weight, whereas in Karen women, the trend in association was similar but not significant (OR 2.36; 95% CI 0.95-5.89). Conclusions: Risk-factor-based screening missed one in four GDM positive women. Considering the benefits of early detection of GDM and the limited additional cost of universal screening, a two-step screening program was implemented.

Vaginal Microbiota and Cytokine Levels Predict Preterm Delivery in Asian Women.

Preterm birth (PTB) is the most common cause of neonatal morbidity and mortality worldwide. Approximately half of PTBs is linked with microbial etiologies, including pathologic changes to the vaginal microbiota, which vary according to ethnicity. Globally more than 50% of PTBs occur in Asia, but studies of the vaginal microbiome and its association with pregnancy outcomes in Asian women are lacking. This study aimed to longitudinally analyzed the vaginal microbiome and cytokine environment of 18 Karen and Burman pregnant women who delivered preterm and 36 matched controls delivering at full term. Using 16S ribosomal RNA gene sequencing we identified a predictive vaginal microbiota signature for PTB that was detectable as early as the first trimester of pregnancy, characterized by higher levels of Prevotella buccalis, and lower levels of Lactobacillus crispatus and Finegoldia, accompanied by decreased levels of cytokines including IFNγ, IL-4, and TNFα. Differences in the vaginal microbial diversity and local vaginal immune environment were associated with greater risk of preterm birth. Our findings highlight new opportunities to predict PTB in Asian women in low-resource settings who are at highest risk of adverse outcomes from unexpected PTB, as well as in Burman/Karen ethnic minority groups in high-resource regions.

A Neutrophil-Driven Inflammatory Signature Characterizes the Blood Transcriptome Fingerprint of Psoriasis.

Transcriptome profiling approaches have been widely used to investigate the mechanisms underlying psoriasis pathogenesis. Most researchers have measured changes in transcript abundance in skin biopsies; relatively few have examined transcriptome changes in the blood. Although less relevant to the study of psoriasis pathogenesis, blood transcriptome profiles can be readily compared across various diseases. Here, we used a pre-established set of 382 transcriptional modules as a common framework to compare changes in blood transcript abundance in two independent public psoriasis datasets. We then compared the resulting "transcriptional fingerprints" to those obtained for a reference set of 16 pathological or physiological states. The perturbations in blood transcript abundance in psoriasis were relatively subtle compared to the changes we observed in other autoimmune and auto-inflammatory diseases. However, we did observe a consistent pattern of changes for a set of modules associated with neutrophil activation and inflammation; interestingly, this pattern resembled that observed in patients with Kawasaki disease. This similarity between the blood-transcriptome signatures in psoriasis and Kawasaki disease suggests that the immune mechanisms driving their pathogenesis might be partially shared.

Definition of erythroid cell-positive blood transcriptome phenotypes associated with severe respiratory syncytial virus infection.

Biomarkers to assess the risk of developing severe respiratory syncytial virus (RSV) infection are needed. We conducted a meta-analysis of 490 unique profiles from six public RSV blood transcriptome datasets. A repertoire of 382 well-characterized transcriptional modules was used to define dominant host responses to RSV infection. The consolidated RSV cohort was stratified according to four traits: "interferon response" (IFN), "neutrophil-driven inflammation" (Infl), "cell cycle" (CC), and "erythrocytes" (Ery). We identified eight prevalent blood transcriptome phenotypes, of which three Ery+ phenotypes comprised higher proportions of patients requiring intensive care. This finding confirms on a larger scale data from one of our earlier reports describing an association between an erythrocyte signature and RSV disease severity. Further contextual interpretation made it possible to associate this signature with immunosuppressive states (late stage cancer, pharmacological immunosuppression), and with a population of fetal glycophorin A+ erythroid precursors. Furthermore, we posit that this erythrocyte cell signature may be linked to a population of immunosuppressive erythroid cells previously described in the literature, and that overabundance of this cell population in RSV patients may underlie progression to severe disease. These findings outline potential priority areas for biomarker development and investigations into the immune biology of RSV infection. The approach that we developed and employed here should also permit to delineate prevalent blood transcriptome phenotypes in other settings.

Blood gene transcript signature profiling in pregnancies resulting in preterm birth: A systematic review.

OBJECTIVE: To pursue a systematic review and summarise the current evidence for the potential of transcriptome molecular profiling in investigating the preterm phenotype. STUDY DESIGN: We systematically reviewed the literature, using readily available electronic databases (i.e. PubMed/Medline, Embase, Scopus and Web of Science) from inception until March 2020 to identify investigations of maternal blood-derived RNA profiling in preterm birth (PTB). Studies were included if circulating coding or non-coding RNA was analysed in maternal blood during pregnancy and/or at delivery. Interventional trials were not included. The primary outcome was the availability of whole genome expression patterns evaluated in pregnancies resulting in preterm deliveries. RESULTS: A total of 35 articles were included in the final analysis. Most of the studies were conducted in high-income countries and published in the last decade. Apart from spontaneous PTB, a variety of phenotypes leading to preterm delivery were reported. Differences in sampling methods, target gene selection and laboratory protocols severely limited any quantitative comparisons. Most of the studies revealed that gene expression profiling during pregnancy has high potential for identifying women at risk of spontaneous and/or non-spontaneous PTB as early as in the first trimester. CONCLUSION: Assessing maternal blood-derived transcriptional signatures for PTB risk in pregnant women holds promise as a screening approach. However, longitudinally followed, prospective pregnancy cohorts are lacking. These are relevant for identifying causes leading to PTB and whether prediction of spontaneous PTB or co-morbidities associated with PTB is achievable. More emphasis on widely employed standardised protocols is required to ensure comparability of results.

Role of QuantiFERON-TB Gold antigen-specific IL-1ß in diagnosis of active tuberculosis.

The main objective of the study was to evaluate whether in vitro QuantiFERON-TB Gold In-Tube (QFT-GIT) assay antigen-specific IL-1ß, TNF-α, IL-2, IL-6, IL-8 and IL-12 (p40) production is associated with active TB. In a cohort of 77 pulmonary TB patients (PTB), 67 healthy household contacts (HHC) and 83 healthy control subjects (HCS), the antigen-specific cytokines levels were determined in supernatants generated from QFT-GIT tubes. Antigen-specific IL-1ß levels were significantly higher in PTB than HHC and HCS. At a fixed cutoff point (1,108 pg/ml), IL-1ß showed positivity of 62.33% in PTB, 22.38% in HHC and 22.89% in HCS. Moreover, antigen-specific IL-1ß assay can differentiate PTB and HHC (believed to be latently infected) (p < 0.0001). Like IL-1ß, significantly higher levels of antigen-specific TNF-α were associated with PTB and displayed 43.63% positivity in PTB. The antigen-specific IL-2 levels were associated both with PTB (54.54%) and HHC (48.14%). Other cytokines levels did not differ among the groups. Our results suggest that antigen-specific IL-1ß can be used as a biomarker for active TB diagnosis as well as for differential diagnosis of PTB and LTBI.

A toolbox for tuberculosis (TB) diagnosis: an Indian multi-centric study (2006-2008); evaluation of serological assays based on PGL-Tb1 and ESAT-6/CFP10 antigens for TB diagnosis.

BACKGROUND: The aim of this multi-centric prospective study in India was to assess the accuracy of a serological test as an additional tool for diagnosing active tuberculosis (ATB). In particular, an assay based on ELISA using a phenolic glycolipid (PGL-Tb1) or a fusion protein (ESAT-6/CFP10) was compared to the tuberculin skin test (TST) and the microbiological results according to HIV status. METHODS: Individuals with and without ATB and HIV infection were enrolled. Serology and TST results were analyzed per se and in combination with the microbiological data. RESULTS: Among the 778 ATB patients, 102 were HIV-infected, 316 HIV-uninfected and 360 had an HIV-unknown status. Of the 945 non-ATB subjects, 559 were at low risk (community adults) and 386 at high risk of M. tuberculosis exposure. Among those with ATB, the sensitivity of ELISA-PGL-Tb1 for ATB was higher than that of ELISA-ESAT-6/CFP10, both in HIV-infected (72.3% versus 63.7%, p = 0.29) and HIV-uninfected/HIV-unknown groups (40.5% versus 28.6%; p<0.0001), whereas the specificity was around 91% for both tests. Sensitivity for ATB increased when the results of the two ELISA were combined, reaching 75.5% in the HIV-infected and 50.9% in the group of HIV-uninfected/HIV-unknown ATB, with a significant decrease of the global specificity (83.9%). Analyzing the ELISA results with the microbiological results, we observed that the sensitivity of both serology tests was independent of the ATB patients' smear microscopy (SM) status and grade. Combining the results of SM with both ELISA, the detection of ATB patients significantly increased (p<0.0001), particularly in those with extrapulmonary TB (up to 45.1%) or HIV infection (up to 83.3%). No significant association was observed between TST and serology results. CONCLUSIONS: In this prospective multi-centric study, the combination of two rapid tests, such as SM and serology, might be useful in detecting ATB, especially in HIV-infected patients.

A toolbox for tuberculosis (TB) diagnosis: an Indian multicentric study (2006-2008). Evaluation of QuantiFERON-TB gold in tube for TB diagnosis.

BACKGROUND: The aim of this multicentric prospective study in India was to assess the performance of the QuantiFERON TB-Gold in tube (QFT-GIT), Tuberculin Skin Test (TST) and microbiological results as additional tools for diagnosing active tuberculosis (TB) and latent infection (LTBI) according to Human Immunodeficiency Virus (HIV) status. METHODS: Individuals with and without active TB and HIV infection were enrolled between 2006-2008. QFT-GIT and TST results were analyzed per se and in combination with microbiological data. RESULTS: Among the 276 individuals (96 active pulmonary TB and 180 no active TB) tested by QFT-GIT, 18 indeterminate results (6.5%) were found, more significantly numerous in the HIV-infected (15/92; 16.3%) than the HIV-uninfected (3/184; 1.6%)(p<0.0001). QFT-GIT sensitivity for active TB was 82.3% and 92.9% respectively after including or excluding indeterminate results. Clinical sensitivity was significantly lower in the HIV-infected (68.4%) than the HIV-uninfected (91.4%) patients (p = 0.0059). LTBI was detected in 49.3% of subjects without active TB but varied according to TB exposure. When the TST and QFT-GIT were concomitantly performed, the respective sensitivity for active TB diagnosis was 95.0% and 85.0% in the HIV-uninfected (p = 0.60), and 66.7% and 51.5% in the HIV-infected patients (p = 0.32). QFT-GIT and TST respective specificity for active TB in the HIV-uninfected was 25.0% and 57.1% (p = 0.028), and 64.8% and 83.3% in the HIV-infected (p = 0.047). In those with active TB, QFT-GIT results were not associated with microbiological parameters (smear grade, liquid culture status, time-to-positivity of culture) or clinical suspicion of active TB score (provided by the clinicians at enrollment). Combining microbiological tests with both immunological tests significantly increased sensitivity for active TB diagnosis (p = 0.0002), especially in the HIV-infected individuals (p = 0.0016). CONCLUSION: QFT-GIT and TST have similar diagnostic value for active TB diagnosis. In HIV-infected patients, combining microbiological tests with both immunological tests significantly increases the sensitivity for active TB diagnosis.

A toolbox for tuberculosis diagnosis: an Indian multicentric study (2006-2008): microbiological results.

BACKGROUND: The aim of this multicentric prospective study in India was to assess the value of several microbiological tools that contribute to the diagnosis of tuberculosis (TB) according to HIV status. METHODS: Standard microbiological tools on individual specimens were analyzed. RESULTS: Among the 807 patients with active TB, 131 were HIV-infected, 316 HIV-uninfected and 360 had HIV-unknown status. Among the 980 non-active TB subjects, 559 were at low risk and 421 were at high risk of M. tuberculosis (Mtb) exposure. Sensitivity of smear microscopy (SM) was significantly lower in HIV-infected (42.2%) than HIV-uninfected (75.9%) (p = 0.0001) and HIV-unknown pulmonary TB patients (61.4%) (p = 0.004). Specificity was 94.5% in non-TB patients and 100% in health care workers (HCW) and healthy family contacts. Automated liquid culture has significantly higher diagnostic performances than solid culture, measured by sensitivity (74.7% vs. 55.9%) (p = 0.0001) and shorter median time to detection (TTD) (12.0 vs. 34.0 days) (p = 0.0001). Specificity was 100% in HCW and cured-TB patients, but was lower in non-TB patients (89%) due to isolation of Mycobacteria other than tuberculosis (MOTT). TTD by both methods was related to AFB score. Contamination rate was low (1.4%). AccuProbe hybridization technique detected Mtb in almost all culture-positive specimens, but MOTT were found in 4.7% with a significantly higher frequency in HIV-infected (15%) than HIV-uninfected TB patients (0.5%) (p = 0.0007). Pre-test classification significantly increased the diagnostic value of all microbiological tests in pulmonary TB patients (p<0.0001) but to a lesser degree in extrapulmonary TB patients. CONCLUSIONS: Conventional microbiological tools led to results similar to those already described in India special features for HIV-infected TB patients included lower detection by SM and culture. New microbiological assays, such as the automated liquid culture system, showed increased accuracy and speed of detection.

Comparison of interferon gamma-inducible protein-10 and interferon gamma-based QuantiFERON TB Gold assays with tuberculin skin test in HIV-infected subjects.

We aimed to compare the positivity of the QuantiFERON TB gold in-tube (QFT-IT antigens) specific interferon gamma (IFN-γ/QFT-IT) and IFN-γ-inducible protein-10 (IP-10/QFT-IT) assays with tuberculin skin test (TST) among human immunodeficiency virus (HIV)-infected individuals in a TB endemic setting. A total of 180 HIV-infected subjects, with no evidence of active TB, were recruited. IFN-γ and IP-10 levels specific to QFT-IT antigens were measured in plasma from QFT-IT tubes. The overall positivity of TST at the 5-mm cut-off point (19%) was significantly lower when compared to IFN-γ/QFT-IT (38%) and IP-10/QFT-IT (45%) assays. The positivity of IP-10/QFT-IT was significantly higher than that of IFN-γ/QFT-IT (P = 0.038). Indeterminate results for IFN-γ/QFT-IT and IP-10/QFT-IT were more frequent in subjects with CD4 count <100 cells/µL than in those with >100 cells/µL. IFN-γ/QFT-IT (9%) yielded significantly higher number of indeterminate results than IP-10/QFT-IT (5%). The frequency of these responses is higher than the proportion of individuals with positive TST results. However, 6 IFN-γ/QFT-IT- or IP-10/QFT-IT-negative subjects were positive for TST at the 5-mm cut-off point. Prospective and prognostic studies are required to clarify the significance of these data.

IP-10 response to RD1 antigens might be a useful biomarker for monitoring tuberculosis therapy.

BACKGROUND: There is an urgent need of prognosis markers for tuberculosis (TB) to improve treatment strategies. The results of several studies show that the Interferon (IFN)-γ-specific response to the TB antigens of the QuantiFERON TB Gold (QFT-IT antigens) decreases after successful TB therapy. The objective of this study was to evaluate whether there are factors other than IFN-γ [such as IFN-γ inducible protein (IP)-10 which has also been associated with TB] in response to QFT-IT antigens that can be used as biomarkers for monitoring TB treatment. METHODS: In this exploratory study we assessed the changes in IP-10 secretion in response to QFT-IT antigens and RD1 peptides selected by computational analysis in 17 patients with active TB at the time of diagnosis and after 6 months of treatment. The IFN-γ response to QFT-IT antigens and RD1 selected peptides was evaluated as a control. A non-parametric Wilcoxon signed-rank test for paired comparisons was used to compare the continuous variables at the time of diagnosis and at therapy completion. A Chi-square test was used to compare proportions. RESULTS: We did not observe significant IP-10 changes in whole blood from either NIL or QFT-IT antigen tubes, after 1-day stimulation, between baseline and therapy completion (p = 0.08 and p = 0.7 respectively). Conversely, the level of IP-10 release to RD1 selected peptides was significantly different (p = 0.006). Similar results were obtained when we detected the IFN-γ in response to the QFT-IT antigens (p = 0.06) and RD1 selected peptides (p = 0.0003). The proportion of the IP-10 responders to the QFT-IT antigens did not significantly change between baseline and therapy completion (p = 0.6), whereas it significantly changed in response to RD1 selected peptides (p = 0.002). The proportion of IFN-γ responders between baseline and therapy completion was not significant for QFT-IT antigens (p = 0.2), whereas it was significant for the RD1 selected peptides (p = 0.002), confirming previous observations. CONCLUSIONS: Our preliminary study provides an interesting hypothesis: IP-10 response to RD1 selected peptides (similar to IFN-γ) might be a useful biomarker for monitoring therapy efficacy in patients with active TB. However, further studies in larger cohorts are needed to confirm the consistency of these study results.