Clonal chromosomal mosaicism and loss of chromosome Y in elderly men increase vulnerability for SARS-CoV-2

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, COVID-19) had an estimated overall case fatality ratio of 1.38% (pre-vaccination), being 53% higher in males and increasing exponentially with age. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, we found 133 cases (1.42%) with detectable clonal mosaicism for chromosome alterations (mCA) and 226 males (5.08%) with acquired loss of chromosome Y (LOY). Individuals with clonal mosaic events (mCA and/or LOY) showed a 54% increase in the risk of COVID-19 lethality. LOY is associated with transcriptomic biomarkers of immune dysfunction, pro-coagulation activity and cardiovascular risk. Interferon-induced genes involved in the initial immune response to SARS-CoV-2 are also down-regulated in LOY. Thus, mCA and LOY underlie at least part of the sex-biased severity and mortality of COVID-19 in aging patients. Given its potential therapeutic and prognostic relevance, evaluation of clonal mosaicism should be implemented as biomarker of COVID-19 severity in elderly people. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, individuals with clonal mosaic events (clonal mosaicism for chromosome alterations and/or loss of chromosome Y) showed an increased risk of COVID-19 lethality

Evaluation of the transcriptional immune biomarkers in peripheral blood from Warao indigenous associate with the infection by Mycobacterium tuberculosis

Abstract INTRODUCTION: Biomarkers are critical tools for finding new approaches for controlling the spread of tuberculosis (TB), including for predicting the development of TB therapeutics, vaccines, and diagnostic tools. METHODS: Expression of immune biomarkers was analyzed in peripheral blood cells stimulated and non-stimulated with M. tuberculosis antigens ESAT-6, CFP10 and TB7.7. in Warao indigenous individuals. These biomarkers may be able to differentiate TB states, such as active tuberculosis (ATB) cases and latent tuberculosis infection (LTBI) from non-infected controls (NIC). A real-time reverse transcription polymerase chain reaction (RT-qPCR) assay was performed on 100 blood samples under non-stimulation or direct ex vivo conditions (NS=50) and stimulation conditions (S=50). RESULTS: The findings are shown as the median and interquartile range (IQR) of relative gene expression levels of IFN-γ, CD14, MMP9, CCR5, CCL11, CXCL9/MIG, and uPAR/PLAUR immune biomarkers. MMP9 levels were significantly higher in the LTBI-NS and LTBI-S groups compared with the NIC-NS and NIC-S groups. However, CCR5 levels were significantly lower in the LTBI-S group compared with both NIC-NS and NIC-S groups. CCL11 levels were significantly lower in the LTBI-S group compared with the NIC-NS group. CONCLUSIONS: Preliminary findings showed that MMP9 immune biomarkers separated LTBI indigenous individuals from NIC indigenous individuals, while CCR5, CCL11, CD14, and IFN-γ did not differentiate TB states from NIC. MMP9 may be useful as a potential biomarker for LTBI and new infected case detection among Warao indigenous individuals at high risk of developing the disease. It may also be used to halt the epidemic, which will require further validation in larger studies

Diagnostic accuracy of combinations of serological biomarkers for identifying clinical tuberculosis

Introduction: Confirmation of tuberculosis (TB) cases in endemic TB settings is a challenge; obtaining fast and cheap, though accurate, diagnostic tools such as biomarkers is thus urgently needed to enable the early detection of TB. This paper evaluates the diagnostic accuracy of combinations of host serological biomarkers for identifying TB. Methodology: Enzyme-linked immunosorbent assays (ELISA) were used on 70 Venezuelan Creole individuals for evaluating host biomarkers (i.e. CXCL9, sCD14, MMP9 and uPAR proteins) and anti-synthetic peptides covering certain Mycobacterium tuberculosis (Mtb) ESAT-6 (P-12033, P-12034 and P-12037) and Ag85A (P-29878) antigen sequences. The target population consisted of adults having active TB (ATB, n = 28), the tuberculin skin test positive (TST+) or individuals with latent TB infection (LTB, n = 28) and TST- or control subjects (CTRL, n = 14). Results: Receiver operator curve (ROC) analysis revealed good biosignature discriminative ability for 5 serological biomarkers; the accuracy of 3 combinations had a good discriminative ability for diagnosing TB. Anti-P-12034/uPAR detected TB with 96.7% sensitivity and 86.0% specificity, followed by anti-P-12033/uPAR having 96.7% sensitivity and 81.4% specificity. Anti-P-29878/MMP9 had the highest sensitivity (100%), but low specificity (52.17%). Biomarker combinations did not prove efficacious for identifying incipient subclinical TST+TB− subjects at high-risk for TB. Conclusions: The anti-P-12034/uPAR combination could be useful for identifying clinical TB patients. Such an approach holds promise for further validation. © 2018 Araujo et al

Metabolomic Selection in the Progression of Type 2 Diabetes Mellitus: A Genetic Algorithm Approach

According to the World Health Organization (WHO), type 2 diabetes mellitus (T2DM) is a result of the inefficient use of insulin by the body. More than 95% of people with diabetes have T2DM, which is largely due to excess weight and physical inactivity. This study proposes an intelligent feature selection of metabolites related to different stages of diabetes, with the use of genetic algorithms (GA) and the implementation of support vector machines (SVMs), K-Nearest Neighbors (KNNs) and Nearest Centroid (NEARCENT) and with a dataset obtained from the Instituto Mexicano del Seguro Social with the protocol name of the following: “Análisis metabolómico y transcriptómico diferencial en orina y suero de pacientes pre diabéticos, diabéticos y con nefropatía diabética para identificar potenciales biomarcadores pronósticos de daño renal” (differential metabolomic and transcriptomic analyses in the urine and serum of pre-diabetic, diabetic and diabetic nephropathy patients to identify potential prognostic biomarkers of kidney damage). In order to analyze which machine learning (ML) model is the most optimal for classifying patients with some stage of T2DM, the novelty of this work is to provide a genetic algorithm approach that detects significant metabolites in each stage of progression. More than 100 metabolites were identified as significant between all stages; with the data analyzed, the average accuracies obtained in each of the five most-accurate implementations of genetic algorithms were in the range of 0.8214–0.9893 with respect to average accuracy, providing a precise tool to use in detections and backing up a diagnosis constructed entirely with metabolomics. By providing five potential biomarkers for progression, these extremely significant metabolites are as follows: “Cer(d18:1/24:1) i2”, “PC(20:3-OH/P-18:1)”, “Ganoderic acid C2”, “TG(16:0/17:1/18:1)” and “GPEtn(18:0/20:4)”

Ability of innate defence regulator peptides IDR-1002, IDR-HH2 and IDR-1018 to protect against Mycobacterium tuberculosis infections in animal models.

Tuberculosis is an ongoing threat to global health, especially with the emergence of multi drug-resistant (MDR) and extremely drug-resistant strains that are motivating the search for new treatment strategies. One potential strategy is immunotherapy using Innate Defence Regulator (IDR) peptides that selectively modulate innate immunity, enhancing chemokine induction and cell recruitment while suppressing potentially harmful inflammatory responses. IDR peptides possess only modest antimicrobial activity but have profound immunomodulatory functions that appear to be influential in resolving animal model infections. The IDR peptides HH2, 1018 and 1002 were tested for their activity against two M. tuberculosis strains, one drug-sensitive and the other MDR in both in vitro and in vivo models. All peptides showed no cytotoxic activity and only modest direct antimicrobial activity versus M. tuberculosis (MIC of 15-30 µg/ml). Nevertheless peptides HH2 and 1018 reduced bacillary loads in animal models with both the virulent drug susceptible H37Rv strain and an MDR isolate and, especially 1018 led to a considerable reduction in lung inflammation as revealed by decreased pneumonia. These results indicate that IDR peptides have potential as a novel immunotherapy against TB