COVID-19 immune signatures in Uganda persist in HIV co-infection and diverge by pandemic phase.

Little is known about the pathobiology of SARS-CoV-2 infection in sub-Saharan Africa, where severe COVID-19 fatality rates are among the highest in the world and the immunological landscape is unique. In a prospective cohort study of 306 adults encompassing the entire clinical spectrum of SARS-CoV-2 infection in Uganda, we profile the peripheral blood proteome and transcriptome to characterize the immunopathology of COVID-19 across multiple phases of the pandemic. Beyond the prognostic importance of myeloid cell-driven immune activation and lymphopenia, we show that multifaceted impairment of host protein synthesis and redox imbalance define core biological signatures of severe COVID-19, with central roles for IL-7, IL-15, and lymphotoxin-α in COVID-19 respiratory failure. While prognostic signatures are generally consistent in SARS-CoV-2/HIV-coinfection, type I interferon responses uniquely scale with COVID-19 severity in persons living with HIV. Throughout the pandemic, COVID-19 severity peaked during phases dominated by A.23/A.23.1 and Delta B.1.617.2/AY variants. Independent of clinical severity, Delta phase COVID-19 is distinguished by exaggerated pro-inflammatory myeloid cell and inflammasome activation, NK and CD8+ T cell depletion, and impaired host protein synthesis. Combining these analyses with a contemporary Ugandan cohort of adults hospitalized with influenza and other severe acute respiratory infections, we show that activation of epidermal and platelet-derived growth factor pathways are distinct features of COVID-19, deepening translational understanding of mechanisms potentially underlying SARS-CoV-2-associated pulmonary fibrosis. Collectively, our findings provide biological rationale for use of broad and targeted immunotherapies for severe COVID-19 in sub-Saharan Africa, illustrate the relevance of local viral and host factors to SARS-CoV-2 immunopathology, and highlight underemphasized yet therapeutically exploitable immune pathways driving COVID-19 severity.

A Transcriptomic Classifier Model Identifies High-Risk Endotypes in a Prospective Study of Sepsis in Uganda.

OBJECTIVES: In high-income countries (HICs), sepsis endotypes defined by distinct pathobiological mechanisms, mortality risks, and responses to corticosteroid treatment have been identified using blood transcriptomics. The generalizability of these endotypes to low-income and middle-income countries (LMICs), where the global sepsis burden is concentrated, is unknown. We sought to determine the prevalence, prognostic relevance, and immunopathological features of HIC-derived transcriptomic sepsis endotypes in sub-Saharan Africa. DESIGN: Prospective cohort study. SETTING: Public referral hospital in Uganda. PATIENTS: Adults ( n = 128) hospitalized with suspected sepsis. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Using whole-blood RNA sequencing data, we applied 19-gene and 7-gene classifiers derived and validated in HICs (SepstratifieR) to assign patients to one of three sepsis response signatures (SRS). The 19-gene classifier assigned 30 (23.4%), 92 (71.9%), and 6 (4.7%) patients to SRS-1, SRS-2, and SRS-3, respectively, the latter of which is designed to capture individuals transcriptionally closest to health. SRS-1 was defined biologically by proinflammatory innate immune activation and suppressed natural killer-cell, T-cell, and B-cell immunity, whereas SRS-2 was characterized by dampened innate immune activation, preserved lymphocyte immunity, and suppressed transcriptional responses to corticosteroids. Patients assigned to SRS-1 were predominantly (80.0% [24/30]) persons living with HIV with advanced immunosuppression and frequent tuberculosis. Mortality at 30-days differed significantly by endotype and was highest (48.1%) in SRS-1. Agreement between 19-gene and 7-gene SRS assignments was poor (Cohen's kappa 0.11). Patient stratification was suboptimal using the 7-gene classifier with 15.1% (8/53) of individuals assigned to SRS-3 deceased at 30-days. CONCLUSIONS: Sepsis endotypes derived in HICs share biological and clinical features with those identified in sub-Saharan Africa, with major differences in host-pathogen profiles. Our findings highlight the importance of context-specific sepsis endotyping, the generalizability of conserved biological signatures of critical illness across disparate settings, and opportunities to develop more pathobiologically informed sepsis treatment strategies in LMICs.

Correlations between Mental Health, Physical Activity, and Body Composition in American College Students after the COVID-19 Pandemic Lockdown.

Restrictions associated with the COVID-19 pandemic had forced American college students to significantly reduce their daily energy expenditure and increase their sedentary behaviors, thus presumably increasing mental health symptoms, decreasing physical activity levels, and enhancing the promotion of unhealthy eating habits. This study aimed to explore the correlations between mental health symptoms, physical activity levels, and body composition in college students in the years following the pandemic, focusing on the lingering effects of lockdown measures. American college students completed pre-existing, well-validated surveys for both mental health (Hospital Anxiety and Depression Scale) and physical activity (International Physical Activity Questionnaire-Long Form). Body composition was assessed in person with the use of an Inbody 570 device. Of the 90 American college students (M age = 22.52 ± 4.54, 50 females) who participated in this study, depressive and anxious symptom scores consistent with heightened symptomatology were reported by 58% of the participants (N = 52), moderate borderline symptomatology by 17% (N = 15), and asymptomatology by 25% (N = 23). In regard to physical activity, 79% (N = 71) of the students were highly physically active, 18% (N = 16) were moderately active, and 3% (N = 3) reported low levels of physical activity. Additionally, 46% (N = 41) of the students maintained an unhealthy body fat percentage based on the World Health Organization recommendations. Strong, significant relationships were found between anxiety and depression symptomatology and body fat percentage (positive correlation, p = 0.003) and between anxiety and depression symptomatology and skeletal muscle mass (negative correlation, p = 0.015), with said symptomatology increasing with added body fat and decreasing with added skeletal muscle mass. The COVID-19 pandemic lockdown restrictions affected American college students through an increase in mental health symptomatology and a deterioration in overall body composition.

Broad genic repression domains signify enhanced silencing of oncogenes.

Cancers result from a set of genetic and epigenetic alterations. Most known oncogenes were identified by gain-of-function mutations in cancer, yet little is known about their epigenetic features. Through integrative analysis of 11,596 epigenomic profiles and mutations from >8200 tumor-normal pairs, we discover broad genic repression domains (BGRD) on chromatin as an epigenetic signature for oncogenes. A BGRD is a widespread enrichment domain of the repressive histone modification H3K27me3 and is further enriched with multiple other repressive marks including H3K9me3, H3K9me2, and H3K27me2. Further, BGRD displays widespread enrichment of repressed cis-regulatory elements. Shortening of BGRDs is linked to derepression of transcription. BGRDs at oncogenes tend to be conserved across normal cell types. Putative tumor-promoting genes and lncRNAs defined using BGRDs are experimentally verified as required for cancer phenotypes. Therefore, BGRDs play key roles in epigenetic regulation of cancer and provide a direction for mutation-independent discovery of oncogenes.

Machine learning uncovers cell identity regulator by histone code.

Conversion between cell types, e.g., by induced expression of master transcription factors, holds great promise for cellular therapy. Our ability to manipulate cell identity is constrained by incomplete information on cell identity genes (CIGs) and their expression regulation. Here, we develop CEFCIG, an artificial intelligent framework to uncover CIGs and further define their master regulators. On the basis of machine learning, CEFCIG reveals unique histone codes for transcriptional regulation of reported CIGs, and utilizes these codes to predict CIGs and their master regulators with high accuracy. Applying CEFCIG to 1,005 epigenetic profiles, our analysis uncovers the landscape of regulation network for identity genes in individual cell or tissue types. Together, this work provides insights into cell identity regulation, and delivers a powerful technique to facilitate regenerative medicine.

Ssd1 and Gcn2 suppress global translation efficiency in replicatively aged yeast while their activation extends lifespan.

Translational efficiency correlates with longevity, yet its role in lifespan determination remains unclear. Using ribosome profiling, translation efficiency is globally reduced during replicative aging in budding yeast by at least two mechanisms: Firstly, Ssd1 is induced during aging, sequestering mRNAs to P-bodies. Furthermore, Ssd1 overexpression in young cells reduced translation and extended lifespan, while loss of Ssd1 reduced the translational deficit of old cells and shortened lifespan. Secondly, phosphorylation of eIF2α, mediated by the stress kinase Gcn2, was elevated in old cells, contributing to the global reduction in translation without detectable induction of the downstream Gcn4 transcriptional activator. tRNA overexpression activated Gcn2 in young cells and extended lifespan in a manner dependent on Gcn4. Moreover, overexpression of Gcn4 sufficed to extend lifespan in an autophagy-dependent manner in the absence of changes in global translation, indicating that Gcn4-mediated autophagy induction is the ultimate downstream target of activated Gcn2, to extend lifespan.