Cdc73 protects Notch-induced T-cell leukemia cells from DNA damage and mitochondrial stress.

ABSTRACT: Activated Notch signaling is highly prevalent in T-cell acute lymphoblastic leukemia (T-ALL), but pan-Notch inhibitors showed excessive toxicity in clinical trials. To find alternative ways to target Notch signals, we investigated cell division cycle 73 (Cdc73), which is a Notch cofactor and key component of the RNA polymerase-associated transcriptional machinery, an emerging target in T-ALL. Although we confirmed previous work that CDC73 interacts with NOTCH1, we also found that the interaction in T-ALL was context-dependent and facilitated by the transcription factor ETS1. Using mouse models, we showed that Cdc73 is important for Notch-induced T-cell development and T-ALL maintenance. Mechanistically, chromatin and nascent gene expression profiling showed that Cdc73 intersects with Ets1 and Notch at chromatin within enhancers to activate expression of known T-ALL oncogenes through its enhancer functions. Cdc73 also intersects with these factors within promoters to activate transcription of genes that are important for DNA repair and oxidative phosphorylation through its gene body functions. Consistently, Cdc73 deletion induced DNA damage and apoptosis and impaired mitochondrial function. The CDC73-induced DNA repair expression program co-opted by NOTCH1 is more highly expressed in T-ALL than in any other cancer. These data suggest that Cdc73 might induce a gene expression program that was eventually intersected and hijacked by oncogenic Notch to augment proliferation and mitigate the genotoxic and metabolic stresses of elevated Notch signaling. Our report supports studying factors such as CDC73 that intersect with Notch to derive a basic scientific understanding on how to combat Notch-dependent cancers without directly targeting the Notch complex.

Blood transcriptional correlates of BCG-induced protection against tuberculosis in rhesus macaques.

Blood-based correlates of vaccine-induced protection against tuberculosis (TB) are urgently needed. Here, we analyze the blood transcriptome of rhesus macaques immunized with varying doses of intravenous (i.v.) BCG followed by Mycobacterium tuberculosis (Mtb) challenge. We use high-dose i.v. BCG recipients for "discovery" and validate our findings in low-dose recipients and in an independent cohort of macaques receiving BCG via different routes. We identify seven vaccine-induced gene modules, including an innate module (module 1) enriched for type 1 interferon and RIG-I-like receptor signaling pathways. Module 1 on day 2 post-vaccination highly correlates with lung antigen-responsive CD4 T cells at week 8 and with Mtb and granuloma burden following challenge. Parsimonious signatures within module 1 at day 2 post-vaccination predict protection following challenge with area under the receiver operating characteristic curve (AUROC) ≥0.91. Together, these results indicate that the early innate transcriptional response to i.v. BCG in peripheral blood may provide a robust correlate of protection against TB.

Evaluation of chest X-ray with automated interpretation algorithms for mass tuberculosis screening in prisons: a cross-sectional study.

Background: The World Health Organization (WHO) recommends systematic tuberculosis (TB) screening in prisons. Evidence is lacking for accurate and scalable screening approaches in this setting. We aimed to assess the accuracy of artificial intelligence-based chest x-ray interpretation algorithms for TB screening in prisons. Methods: We performed prospective TB screening in three male prisons in Brazil from October 2017 to December 2019. We administered a standardized questionnaire, performed a chest x-ray in a mobile unit, and collected sputum for confirmatory testing using Xpert MTB/RIF and culture. We evaluated x-ray images using three algorithms (CAD4TB version 6, Lunit version 3.1.0.0 and qXR version 3) and compared their accuracy. We utilized multivariable logistic regression to assess the effect of demographic and clinical characteristics on algorithm accuracy. Finally, we investigated the relationship between abnormality scores and Xpert semi-quantitative results. Findings: Among 2075 incarcerated individuals, 259 (12.5%) had confirmed TB. All three algorithms performed similarly overall with area under the receiver operating characteristic curve (AUC) of 0.88-0.91. At 90% sensitivity, only LunitTB and qXR met the WHO Target Product Profile requirements for a triage test, with specificity of 84% and 74%, respectively. All algorithms had variable performance by age, prior TB, smoking, and presence of TB symptoms. LunitTB was the most robust to this heterogeneity but nonetheless failed to meet the TPP for individuals with previous TB. Abnormality scores of all three algorithms were significantly correlated with sputum bacillary load. Interpretation: Automated x-ray interpretation algorithms can be an effective triage tool for TB screening in prisons. However, their specificity is insufficient in individuals with previous TB. Funding: This study was supported by the US National Institutes of Health (grant numbers R01 AI130058 and R01 AI149620) and the State Secretary of Health of Mato Grosso do Sul.

Corrigendum: COVID-19 preventive measures in Northern California jails: Perceived deficiencies, barriers, and unintended harms.

[This corrects the article DOI: 10.3389/fpubh.2022.854343.].

COVID-19 Preventive Measures in Northern California Jails: Perceived Deficiencies, Barriers, and Unintended Harms.

Background: Carceral facilities are high-risk settings for COVID-19 transmission. Little is known about the hidden burden of infection or practical barriers to infection control in these settings, especially in jails. There is also limited research on the mental health impacts of the pandemic among people living and working in carceral facilities. Methods: Between July 8, 2020 and April 30, 2021, we performed SARS-CoV-2 rapid antibody testing and administered a questionnaire among residents and staff of four Northern California jails. We utilized multivariable logistic regression, adjusting for demographic and carceral characteristics, to analyze factors associated with prior infection, including perceived likelihood of prior infection and access to new masks. We additionally assessed the implementation of, perceptions toward, and impacts of COVID-19 policies in practice. We engaged stakeholder representatives, including incarcerated individuals, to guide study design, procedures, and results interpretation. Results: We enrolled 788 jail residents and 380 jail staff. Nearly half of residents and two-thirds of staff who were antibody-positive had not previously tested positive for COVID-19. Among residents without a prior COVID-19 diagnosis, antibody positivity was significantly associated with perceived likelihood of prior infection (adjusted OR = 8.9; 95% CI, 3.6-22.0). Residents who had flu-like illness in jail cited inadequate responses to reported illness and deterrents to symptom reporting, including fears of medical isolation and perceptions of medical neglect. Residents also disclosed deficient access to face masks, which was associated with antibody positivity (adjusted OR = 13.8, 95% CI, 1.8-107.0). Worsened mental health was pervasive among residents, attributed not only to fear of COVID-19 and unsanitary jail conditions but also to intensified isolation and deprivation due to pandemic restrictions on in-person visitation, programs, and recreation time. Conclusion: Carceral settings present significant challenges to maintaining infection control and human rights. Custody officials should work diligently to transform the conditions of medical isolation, which could mitigate deterrents to symptom reporting. Furthermore, they should minimize use of restrictive measures like lockdowns and suspension of visitation that exacerbate the mental health harms of incarceration. Instead, custody officials should ensure comprehensive implementation of other preventive strategies like masking, testing, and vaccination, in conjunction with multisector efforts to advance decarceration.

The role of prisons in disseminating tuberculosis in Brazil: A genomic epidemiology study.

Background: Globally, prisons are high-incidence settings for tuberculosis. Yet the role of prisons as reservoirs of M. tuberculosis, propagating epidemics through spillover to surrounding communities, has been difficult to measure directly. Methods: To quantify the role of prisons in driving wider community M. tuberculosis transmission, we conducted prospective genomic surveillance in Central West Brazil from 2014 to 2019. We whole genome sequenced 1152 M. tuberculosis isolates collected during active and passive surveillance inside and outside prisons and linked genomes to detailed incarceration histories. We applied multiple phylogenetic and genomic clustering approaches and inferred timed transmission trees. Findings: M. tuberculosis sequences from incarcerated and non-incarcerated people were closely related in a maximum likelihood phylogeny. The majority (70.8%; 46/65) of genomic clusters including people with no incarceration history also included individuals with a recent history of incarceration. Among cases in individuals with no incarceration history, 50.6% (162/320) were in clusters that included individuals with recent incarceration history, suggesting that transmission chains often span prisons and communities. We identified a minimum of 18 highly probable spillover events, M. tuberculosis transmission from people with a recent incarceration history to people with no prior history of incarceration, occurring in the state's four largest cities and across sampling years. We additionally found that frequent transfers of people between the state's prisons creates a highly connected prison network that likely disseminates M. tuberculosis across the state. Interpretation: We developed a framework for measuring spillover from high-incidence environments to surrounding communities by integrating genomic and spatial information. Our findings indicate that, in this setting, prisons serve not only as disease reservoirs, but also disseminate M. tuberculosis across highly connected prison networks, both amplifying and propagating M. tuberculosis risk in surrounding communities. Funding: Brazil's National Council for Scientific and Technological Development and US National Institutes of Health.

Factors associated with COVID-19 vaccine acceptance and hesitancy among residents of Northern California jails.

Carceral facilities are high-risk settings for COVID-19 transmission. Factors associated with COVID-19 vaccine acceptance and hesitancy among incarcerated individuals are poorly understood, especially among jail residents. Here, we conducted a retrospective review of electronic health record (EHR) data on COVID-19 vaccine uptake in custody and additionally administered a survey to assess reasons for vaccine hesitancy, sources of COVID-19 information, and medical mistrust among residents of four Northern California jails. We performed multivariate logistic regression to determine associations with vaccine acceptance. Of 2,564 jail residents offered a COVID-19 vaccine between March 19, 2021 and June 30, 2021, 1,441 (56.2%) accepted at least one dose. Among vaccinated residents, 497 (34.5%) had initially refused. Vaccine uptake was higher among older individuals, women, those with recent flu vaccination, and those living in shared housing. Among 509 survey respondents, leading reasons for vaccine hesitancy were concerns around side effects and suboptimal efficacy, with cost and the need for an annual booster being other hypothetical deterrents to vaccination. Vaccine hesitancy was also associated with mistrust of medical personnel in and out of jail, although this association varied by race/ethnicity. Television and friends/family were the most common and most trusted sources of COVID-19 information, respectively. Overall, vaccine acceptance was much lower among jail residents than the local and national general population. Interventions to increase vaccination rates in this setting should utilize accessible and trusted sources of information to address concerns about side effects and efficacy, while working to mitigate medical and institutional mistrust among residents.

An 8-gene machine learning model improves clinical prediction of severe dengue progression.

BACKGROUND: Each year 3-6 million people develop life-threatening severe dengue (SD). Clinical warning signs for SD manifest late in the disease course and are nonspecific, leading to missed cases and excess hospital burden. Better SD prognostics are urgently needed. METHODS: We integrated 11 public datasets profiling the blood transcriptome of 365 dengue patients of all ages and from seven countries, encompassing biological, clinical, and technical heterogeneity. We performed an iterative multi-cohort analysis to identify differentially expressed genes (DEGs) between non-severe patients and SD progressors. Using only these DEGs, we trained an XGBoost machine learning model on public data to predict progression to SD. All model parameters were "locked" prior to validation in an independent, prospectively enrolled cohort of 377 dengue patients in Colombia. We measured expression of the DEGs in whole blood samples collected upon presentation, prior to SD progression. We then compared the accuracy of the locked XGBoost model and clinical warning signs in predicting SD. RESULTS: We identified eight SD-associated DEGs in the public datasets and built an 8-gene XGBoost model that accurately predicted SD progression in the independent validation cohort with 86.4% (95% CI 68.2-100) sensitivity and 79.7% (95% CI 75.5-83.9) specificity. Given the 5.8% proportion of SD cases in this cohort, the 8-gene model had a positive and negative predictive value (PPV and NPV) of 20.9% (95% CI 16.7-25.6) and 99.0% (95% CI 97.7-100.0), respectively. Compared to clinical warning signs at presentation, which had 77.3% (95% CI 58.3-94.1) sensitivity and 39.7% (95% CI 34.7-44.9) specificity, the 8-gene model led to an 80% reduction in the number needed to predict (NNP) from 25.4 to 5.0. Importantly, the 8-gene model accurately predicted subsequent SD in the first three days post-fever onset and up to three days prior to SD progression. CONCLUSIONS: The 8-gene XGBoost model, trained on heterogeneous public datasets, accurately predicted progression to SD in a large, independent, prospective cohort, including during the early febrile stage when SD prediction remains clinically difficult. The model has potential to be translated to a point-of-care prognostic assay to reduce dengue morbidity and mortality without overwhelming limited healthcare resources.

A 6-mRNA host response classifier in whole blood predicts outcomes in COVID-19 and other acute viral infections.

Predicting the severity of COVID-19 remains an unmet medical need. Our objective was to develop a blood-based host-gene-expression classifier for the severity of viral infections and validate it in independent data, including COVID-19. We developed a logistic regression-based classifier for the severity of viral infections and validated it in multiple viral infection settings including COVID-19. We used training data (N = 705) from 21 retrospective transcriptomic clinical studies of influenza and other viral illnesses looking at a preselected panel of host immune response messenger RNAs. We selected 6 host RNAs and trained logistic regression classifier with a cross-validation area under curve of 0.90 for predicting 30-day mortality in viral illnesses. Next, in 1417 samples across 21 independent retrospective cohorts the locked 6-RNA classifier had an area under curve of 0.94 for discriminating patients with severe vs. non-severe infection. Next, in independent cohorts of prospectively (N = 97) and retrospectively (N = 100) enrolled patients with confirmed COVID-19, the classifier had an area under curve of 0.89 and 0.87, respectively, for identifying patients with severe respiratory failure or 30-day mortality. Finally, we developed a loop-mediated isothermal gene expression assay for the 6-messenger-RNA panel to facilitate implementation as a rapid assay. With further study, the classifier could assist in the risk assessment of COVID-19 and other acute viral infections patients to determine severity and level of care, thereby improving patient management and reducing healthcare burden.

All-cause and cause-specific mortality during and following incarceration in Brazil: A retrospective cohort study.

BACKGROUND: Mortality during and after incarceration is poorly understood in low- and middle-income countries (LMICs). The need to address this knowledge gap is especially urgent in South America, which has the fastest growing prison population in the world. In Brazil, insufficient data have precluded our understanding of all-cause and cause-specific mortality during and after incarceration. METHODS AND FINDINGS: We linked incarceration and mortality databases for the Brazilian state of Mato Grosso do Sul to obtain a retrospective cohort of 114,751 individuals with recent incarceration. Between January 1, 2009 and December 31, 2018, we identified 3,127 deaths of individuals with recent incarceration (705 in detention and 2,422 following release). We analyzed age-standardized, all-cause, and cause-specific mortality rates among individuals detained in different facility types and following release, compared to non-incarcerated residents. We additionally modeled mortality rates over time during and after incarceration for all causes of death, violence, or suicide. Deaths in custody were 2.2 times the number reported by the national prison administration (n = 317). Incarcerated men and boys experienced elevated mortality, compared with the non-incarcerated population, due to increased risk of death from violence, suicide, and communicable diseases, with the highest standardized incidence rate ratio (IRR) in semi-open prisons (2.4; 95% confidence interval [CI]: 2.0 to 2.8), police stations (3.1; 95% CI: 2.5 to 3.9), and youth detention (8.1; 95% CI: 5.9 to 10.8). Incarcerated women experienced increased mortality from suicide (IRR = 6.0, 95% CI: 1.2 to 17.7) and communicable diseases (IRR = 2.5, 95% CI: 1.1 to 5.0). Following release from prison, mortality was markedly elevated for men (IRR = 3.0; 95% CI: 2.8 to 3.1) and women (IRR = 2.4; 95% CI: 2.1 to 2.9). The risk of violent death and suicide was highest immediately post-release and declined over time; however, all-cause mortality remained elevated 8 years post-release. The limitations of this study include inability to establish causality, uncertain reliability of data during incarceration, and underestimation of mortality rates due to imperfect database linkage. CONCLUSIONS: Incarcerated individuals in Brazil experienced increased mortality from violence, suicide, and communicable diseases. Mortality was heightened following release for all leading causes of death, with particularly high risk of early violent death and elevated all-cause mortality up to 8 years post-release. These disparities may have been underrecognized in Brazil due to underreporting and insufficient data.

Loss of Extreme Long-Range Enhancers in Human Neural Crest Drives a Craniofacial Disorder.

Non-coding mutations at the far end of a large gene desert surrounding the SOX9 gene result in a human craniofacial disorder called Pierre Robin sequence (PRS). Leveraging a human stem cell differentiation model, we identify two clusters of enhancers within the PRS-associated region that regulate SOX9 expression during a restricted window of facial progenitor development at distances up to 1.45 Mb. Enhancers within the 1.45 Mb cluster exhibit highly synergistic activity that is dependent on the Coordinator motif. Using mouse models, we demonstrate that PRS phenotypic specificity arises from the convergence of two mechanisms: confinement of Sox9 dosage perturbation to developing facial structures through context-specific enhancer activity and heightened sensitivity of the lower jaw to Sox9 expression reduction. Overall, we characterize the longest-range human enhancers involved in congenital malformations, directly demonstrate that PRS is an enhanceropathy, and illustrate how small changes in gene expression can lead to morphological variation.