Global disease burden of and risk factors for acute lower respiratory infections caused by respiratory syncytial virus in preterm infants and young children in 2019: a systematic review and meta-analysis of aggregated and individual participant data.

BACKGROUND: Infants and young children born prematurely are at high risk of severe acute lower respiratory infection (ALRI) caused by respiratory syncytial virus (RSV). In this study, we aimed to assess the global disease burden of and risk factors for RSV-associated ALRI in infants and young children born before 37 weeks of gestation. METHODS: We conducted a systematic review and meta-analysis of aggregated data from studies published between Jan 1, 1995, and Dec 31, 2021, identified from MEDLINE, Embase, and Global Health, and individual participant data shared by the Respiratory Virus Global Epidemiology Network on respiratory infectious diseases. We estimated RSV-associated ALRI incidence in community, hospital admission, in-hospital mortality, and overall mortality among children younger than 2 years born prematurely. We conducted two-stage random-effects meta-regression analyses accounting for chronological age groups, gestational age bands (early preterm, <32 weeks gestational age [wGA], and late preterm, 32 to <37 wGA), and changes over 5-year intervals from 2000 to 2019. Using individual participant data, we assessed perinatal, sociodemographic, and household factors, and underlying medical conditions for RSV-associated ALRI incidence, hospital admission, and three severity outcome groups (longer hospital stay [>4 days], use of supplemental oxygen and mechanical ventilation, or intensive care unit admission) by estimating pooled odds ratios (ORs) through a two-stage meta-analysis (multivariate logistic regression and random-effects meta-analysis). This study is registered with PROSPERO, CRD42021269742. FINDINGS: We included 47 studies from the literature and 17 studies with individual participant-level data contributed by the participating investigators. We estimated that, in 2019, 1 650 000 (95% uncertainty range [UR] 1 350 000-1 990 000) RSV-associated ALRI episodes, 533 000 (385 000-730 000) RSV-associated hospital admissions, 3050 (1080-8620) RSV-associated in-hospital deaths, and 26 760 (11 190-46 240) RSV-attributable deaths occurred in preterm infants worldwide. Among early preterm infants, the RSV-associated ALRI incidence rate and hospitalisation rate were significantly higher (rate ratio [RR] ranging from 1·69 to 3·87 across different age groups and outcomes) than for all infants born at any gestational age. In the second year of life, early preterm infants and young children had a similar incidence rate but still a significantly higher hospitalisation rate (RR 2·26 [95% UR 1·27-3·98]) compared with all infants and young children. Although late preterm infants had RSV-associated ALRI incidence rates similar to that of all infants younger than 1 year, they had higher RSV-associated ALRI hospitalisation rate in the first 6 months (RR 1·93 [1·11-3·26]). Overall, preterm infants accounted for 25% (95% UR 16-37) of RSV-associated ALRI hospitalisations in all infants of any gestational age. RSV-associated ALRI in-hospital case fatality ratio in preterm infants was similar to all infants. The factors identified to be associated with RSV-associated ALRI incidence were mainly perinatal and sociodemographic characteristics, and factors associated with severe outcomes from infection were mainly underlying medical conditions including congenital heart disease, tracheostomy, bronchopulmonary dysplasia, chronic lung disease, or Down syndrome (with ORs ranging from 1·40 to 4·23). INTERPRETATION: Preterm infants face a disproportionately high burden of RSV-associated disease, accounting for 25% of RSV hospitalisation burden. Early preterm infants have a substantial RSV hospitalisation burden persisting into the second year of life. Preventive products for RSV can have a substantial public health impact by preventing RSV-associated ALRI and severe outcomes from infection in preterm infants. FUNDING: EU Innovative Medicines Initiative Respiratory Syncytial Virus Consortium in Europe.

Multiomics Profiling Reveals Signatures of Dysmetabolism in Urban Populations in Central India.

BACKGROUND: Non-communicable diseases (NCDs) have become a major cause of morbidity and mortality in India. Perturbation of host-microbiome interactions may be a key mechanism by which lifestyle-related risk factors such as tobacco use, alcohol consumption, and physical inactivity may influence metabolic health. There is an urgent need to identify relevant dysmetabolic traits for predicting risk of metabolic disorders, such as diabetes, among susceptible Asian Indians where NCDs are a growing epidemic. METHODS: Here, we report the first in-depth phenotypic study in which we prospectively enrolled 218 adults from urban and rural areas of Central India and used multiomic profiling to identify relationships between microbial taxa and circulating biomarkers of cardiometabolic risk. Assays included fecal microbiota analysis by 16S ribosomal RNA gene amplicon sequencing, quantification of serum short chain fatty acids by gas chromatography-mass spectrometry, and multiplex assaying of serum diabetic proteins, cytokines, chemokines, and multi-isotype antibodies. Sera was also analysed for N-glycans and immunoglobulin G Fc N-glycopeptides. RESULTS: Multiple hallmarks of dysmetabolism were identified in urbanites and young overweight adults, the majority of whom did not have a known diagnosis of diabetes. Association analyses revealed several host-microbe and metabolic associations. CONCLUSIONS: Host-microbe and metabolic interactions are differentially shaped by body weight and geographic status in Central Indians. Further exploration of these links may help create a molecular-level map for estimating risk of developing metabolic disorders and designing early interventions.

Impact of socioeconomic status and living condition on latent tuberculosis diagnosis among the tribal population of Melghat: A cohort study.

AIMS: To study socioeconomic status (SES) and living conditions (LC) as risk factors for latent tuberculosis infection (LTBI) and their impact on QuantiFERON-TB gold (QFT-G) and tuberculin skin test (TST) outcome for determining a better diagnostic test for LTBI in the malnourished tribal population of Melghat. SETTINGS AND DESIGN: Six hundred sixty nine participants matching the inclusion criteria were recruited from 10 tribal villages of Melghat region, India. SUBJECTS AND METHODS: Complete information related to various risk factors and test outcome was obtained on 398 participants, which was analyzed as per predefined conceptual framework. Factors were classified based on their relevance either at individual or household level, and subsequently based on the possibility of intervention. Data were partitioned into concordant and discordant sets depending on test agreement. RESULTS: In concordant set, the two tests revealed that LTBI was significantly associated with smoking (adjusted odds ratio [aOR]: 2.64 [95% confidence interval [CI]: 1.03-6.79]), tobacco usage (aOR: 2.74 [95% CI: 1.50-4.99]), and malnourishment (aOR: 1.97 [95% CI: 1.12-3.48]) after basic adjustment. Inclusion of latent variable SES and LC in the model has mediating effect on the association of above factors with LTBI. Further, the association of SES and LC with LTBI in concordant set was unaltered in presence of other cofactors. From discordant set, results of QFT-G corroborated with that of concordant set. CONCLUSIONS: Poor SES and LC can be considered as strong risk factors linked with LTBI as compared to malnourishment, which is often targeted in such communities. Further, our study showed QFT-G test as a reliable tool in screening of LTBI in the tribal population of Melghat, India.

The assessment of cytokines in Quantiferon supernatants for the diagnosis of latent TB infection in a tribal population of Melghat, India.

The tuberculin skin test (TST) and interferon-gamma release assays (IGRA), namely, the QuantiFERON-TB Gold test (QFT), remain the standard immunological diagnostic tools for latent tuberculosis (TB) infection (LTBI). However, the sub-optimal detection rates of both of these tests are major impediments in recognizing the population at risk. This study was aimed at evaluating additional cytokines besides interferon-gamma (IFN-γ) as biomarkers for improving LTBI diagnosis in the tribal population of Melghat, India. Seventy-four close TB contacts were stratified by QFT and TST results into: (i) QFT+/TST+ (n = 26), (ii) QFT+/TST- (n = 12), (iii) QFT-/TST- (n = 35) and (iv) QFT-/TST+ (n = 1) groups. A panel of cytokines (IL-6, IL-10, TNF-α and IL-2R) was then evaluated in antigen-stimulated QFT cell-free culture supernatants using IMMULITE-1000, an automated immunoassay analyzer. Cytokine estimation showed significantly higher levels of IL-6 in the QFT+/TST+ group, while significantly higher levels of IL-10 were found in the QFT-/TST- group. Correlation analysis identified a positive correlation between IL-6 and the QFT response (r = 0.6723, P < 0.0001), while a negative correlation was seen between QFT and IL-10 expression (r = -0.3271, P = 0.0044). Similarly, IL-6 was positively correlated with TST levels (r = 0.6631, P <0 .0001), and conversely, a negative correlation was found between TST and IL-10 expression (r = -0.5698, P < 0.0001). The positive and negative predictive values of IL-6 were found to be 92.59 and 93.33%, respectively, and the positive and negative predictive values of IL-10 were 96.55 and 91.18%, respectively. No significant impact of the demographic characteristics on cytokine positivity was observed. Our preliminary results suggest that the evaluation of additional cytokines in QFT cell-free culture supernatants may be valuable for the identification of LTBI. Combining IL-6 and IL-10 with QFT and/or TST could markedly improve the detection accuracy of LTBI. Our observations require investigation in larger well-characterized cohorts along with follow-up studies to further confirm the study outcome.

Laboratory investigations on the diagnosis of tuberculosis in the malnourished tribal population of melghat, India.

BACKGROUND: Malnutrition is a major risk factor for the development of tuberculosis (TB). In India, Melghat is among the tribal regions which consist of highest number of malnutrition cases. Because of the paucity of TB data from these malnourished areas there is an urgent need for the development and evaluation of improved TB diagnostic tests. In the present study, three in house developed diagnostic tests namely TB-Ag(antigen) ELISA, Adenosine deaminase (ADA) estimation and IS6110 polymerase chain reaction (PCR) assay were investigated for the detection of Mycobacterium tuberculosis (M. tb.) infection. METHODS: For investigation, blood samples were collected from 128 study subjects from six villages of Melghat tribal area and evaluated using three in house developed assays, namely TB-Ag ELISA, ADA estimation and IS6110 PCR. RESULTS: The TB-Ag ELISA method yielded 83% sensitivity and 94% specificity. The ADA and PCR assay gave a sensitivity of 61% and 49% and specificity of 62% and 98% respectively. A considerable good agreement of 82.81% (k=0.472) between TB-Ag ELISA and PCR was observed. The overall sensitivity of TB-Ag ELISA was significantly higher (p<0.05) than the ADA and PCR while PCR yielded highest specificity among all the three evaluated tests. CONCLUSIONS: We concluded that the routine use of TB-Ag ELISA can be useful for screening of suspected TB patients in the malnourished population where sophisticated laboratory set up is difficult.