Subphenotypes of self-reported symptoms and outcomes in long COVID: a prospective cohort study with latent class analysis.

OBJECTIVE: To characterise subphenotypes of self-reported symptoms and outcomes (SRSOs) in postacute sequelae of COVID-19 (PASC). DESIGN: Prospective, observational cohort study of subjects with PASC. SETTING: Academic tertiary centre from five clinical referral sources. PARTICIPANTS: Adults with COVID-19 ≥20 days before enrolment and presence of any new self-reported symptoms following COVID-19. EXPOSURES: We collected data on clinical variables and SRSOs via structured telephone interviews and performed standardised assessments with validated clinical numerical scales to capture psychological symptoms, neurocognitive functioning and cardiopulmonary function. We collected saliva and stool samples for quantification of SARS-CoV-2 RNA via quantitative PCR. OUTCOMES MEASURES: Description of PASC SRSOs burden and duration, derivation of distinct PASC subphenotypes via latent class analysis (LCA) and relationship with viral load. RESULTS: We analysed baseline data for 214 individuals with a study visit at a median of 197.5 days after COVID-19 diagnosis. Participants reported ever having a median of 9/16 symptoms (IQR 6-11) after acute COVID-19, with muscle-aches, dyspnoea and headache being the most common. Fatigue, cognitive impairment and dyspnoea were experienced for a longer time. Participants had a lower burden of active symptoms (median 3 (1-6)) than those ever experienced (p<0.001). Unsupervised LCA of symptoms revealed three clinically active PASC subphenotypes: a high burden constitutional symptoms (21.9%), a persistent loss/change of smell and taste (20.6%) and a minimal residual symptoms subphenotype (57.5%). Subphenotype assignments were strongly associated with self-assessments of global health, recovery and PASC impact on employment (p<0.001) as well as referral source for enrolment. Viral persistence (5.6% saliva and 1% stool samples positive) did not explain SRSOs or subphenotypes. CONCLUSIONS: We identified three distinct PASC subphenotypes. We highlight that although most symptoms progressively resolve, specific PASC subpopulations are impacted by either high burden of constitutional symptoms or persistent olfactory/gustatory dysfunction, requiring prospective identification and targeted preventive or therapeutic interventions.

The upper and lower respiratory tract microbiome in severe aspiration pneumonia.

Uncertainty persists whether anaerobic bacteria represent important pathogens in aspiration pneumonia. In a nested case-control study of mechanically ventilated patients classified as macro-aspiration pneumonia (MAsP, n = 56), non-macro-aspiration pneumonia (NonMAsP, n = 91), and uninfected controls (n = 11), we profiled upper (URT) and lower respiratory tract (LRT) microbiota with bacterial 16S rRNA gene sequencing, measured plasma host-response biomarkers, analyzed bacterial communities by diversity and oxygen requirements, and performed unsupervised clustering with Dirichlet Multinomial Models (DMM). MAsP and NonMAsP patients had indistinguishable microbiota profiles by alpha diversity and oxygen requirements with similar host-response profiles and 60-day survival. Unsupervised DMM clusters revealed distinct bacterial clusters in the URT and LRT, with low-diversity clusters enriched for facultative anaerobes and typical pathogens, associated with higher plasma levels of SPD and sCD14 and worse 60-day survival. The predictive inter-patient variability in these bacterial profiles highlights the importance of microbiome study in patient sub-phenotyping and precision medicine approaches for severe pneumonia.

Trajectories of Host-Response Subphenotypes in Patients With COVID-19 Across the Spectrum of Respiratory Support.

BACKGROUND: Hospitalized patients with severe COVID-19 follow heterogeneous clinical trajectories, requiring different levels of respiratory support and experiencing diverse clinical outcomes. Differences in host immune responses to SARS-CoV-2 infection may account for the heterogeneous clinical course, but we have limited data on the dynamic evolution of systemic biomarkers and related subphenotypes. Improved understanding of the dynamic transitions of host subphenotypes in COVID-19 may allow for improved patient selection for targeted therapies. RESEARCH QUESTION: We examined the trajectories of host-response profiles in severe COVID-19 and evaluated their prognostic impact on clinical outcomes. STUDY DESIGN AND METHODS: In this prospective observational study, we enrolled 323 inpatients with COVID-19 receiving different levels of baseline respiratory support: (1) low-flow oxygen (37%), (2) noninvasive ventilation (NIV) or high-flow oxygen (HFO; 29%), (3) invasive mechanical ventilation (27%), and (4) extracorporeal membrane oxygenation (7%). We collected plasma samples on enrollment and at days 5 and 10 to measure host-response biomarkers. We classified patients by inflammatory subphenotypes using two validated predictive models. We examined clinical, biomarker, and subphenotype trajectories and outcomes during hospitalization. RESULTS: IL-6, procalcitonin, and angiopoietin 2 persistently were elevated in patients receiving higher levels of respiratory support, whereas soluble receptor of advanced glycation end products (sRAGE) levels displayed the inverse pattern. Patients receiving NIV or HFO at baseline showed the most dynamic clinical trajectory, with 24% eventually requiring intubation and exhibiting worse 60-day mortality than patients receiving invasive mechanical ventilation at baseline (67% vs 35%; P < .0001). sRAGE levels predicted NIV failure and worse 60-day mortality for patients receiving NIV or HFO, whereas IL-6 levels were predictive in all patients regardless of level of support (P < .01). Patients classified to a hyperinflammatory subphenotype at baseline (< 10%) showed worse 60-day survival (P < .0001) and 50% of them remained classified as hyperinflammatory at 5 days after enrollment. INTERPRETATION: Longitudinal study of the systemic host response in COVID-19 revealed substantial and predictive interindividual variability influenced by baseline levels of respiratory support.

Trajectories of host-response biomarkers and inflammatory subphenotypes in COVID-19 patients across the spectrum of respiratory support.

Purpose: Enhanced understanding of the dynamic changes in the dysregulated inflammatory response in COVID-19 may help improve patient selection and timing for immunomodulatory therapies. Methods: We enrolled 323 COVID-19 inpatients on different levels of baseline respiratory support: i) Low Flow Oxygen (37%), ii) Non-Invasive Ventilation or High Flow Oxygen (NIV_HFO, 29%), iii) Invasive Mechanical Ventilation (IMV, 27%), and iv) Extracorporeal Membrane Oxygenation (ECMO, 7%). We collected plasma samples upon enrollment and days 5 and 10 to measure host-response biomarkers. We classified subjects into inflammatory subphenotypes using two validated predictive models. We examined clinical, biomarker and subphenotype trajectories and outcomes during hospitalization. Results: IL-6, procalcitonin, and Angiopoietin-2 were persistently elevated in patients at higher levels of respiratory support, whereas sRAGE displayed the inverse pattern. Patients on NIV_HFO at baseline had the most dynamic clinical trajectory, with 26% eventually requiring intubation and exhibiting worse 60-day mortality than IMV patients at baseline (67% vs. 35%, p<0.0001). sRAGE levels predicted NIV failure and worse 60-day mortality for NIV_HFO patients, whereas IL-6 levels were predictive in IMV or ECMO patients. Hyper-inflammatory subjects at baseline (<10% by both models) had worse 60-day survival (p<0.0001) and 50% of them remained classified as hyper-inflammatory on follow-up sampling at 5 days post-enrollment. Receipt of combined immunomodulatory therapies (steroids and anti-IL6 agents) was associated with markedly increased IL-6 and lower Angiopoietin-2 levels (p<0.05). Conclusions: Longitudinal study of systemic host responses in COVID-19 revealed substantial and predictive inter-individual variability, influenced by baseline levels of respiratory support and concurrent immunomodulatory therapies.

Gut and oral microbiota associations with viral mitigation behaviors during the COVID-19 pandemic.

Imposition of social and health behavior mitigations are important control measures in response to the coronavirus disease 2019 (COVID-19) pandemic caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Although postulated that these measures may impact the human microbiota including losses in diversity from heightened hygiene and social distancing measures, this hypothesis remains to be tested. Other impacts on the microbiota and host mental and physical health status associations from these measures are also not well-studied. Here we examine changes in stool and oral microbiota by analyzing 16S rRNA gene sequence taxonomic profiles from the same individuals during pre-pandemic (before March 2020) and early pandemic (May-November 2020) phases. During the early pandemic phase, individuals were also surveyed using questionnaires to report health histories, anxiety, depression, sleep and other lifestyle behaviors in a cohort of predominantly Caucasian adults (mean age = 61.5 years) with the majority reporting at least one underlying co-morbidity. We identified changes in microbiota (stool n = 288; oral n = 89) between pre-pandemic and early pandemic time points from the same subject and associated these differences with questionnaire responses using linear statistical models and hierarchical clustering of microbiota composition coupled to logistic regression. While a trend in loss of diversity was identified between pre-pandemic and early pandemic time points it was not statistically significant. Paired difference analyses between individuals identified fewer significant changes between pre-pandemic and early pandemic microbiota in those who reported fewer comorbidities. Cluster transition analyses of stool and saliva microbiota determined most individuals remained in the same cluster assignments from the pre-pandemic to early pandemic period. Individuals with microbiota that shifted in composition, causing them to depart a pre-pandemic cluster, reported more health issues and pandemic-associated worries. Collectively, our study identified that stool and saliva microbiota from the pre-pandemic to early pandemic periods largely exhibited ecological stability (especially stool microbiota) with most associations in loss of diversity or changes in composition related to more reported health issues and pandemic-associated worries. Longitudinal observational cohorts are necessary to monitor the microbiome in response to pandemics and changes in public health measures.

Pulmonary Function Trajectories in People with HIV: Analysis of the Pittsburgh HIV Lung Cohort.

Rationale: Human immunodeficiency virus (HIV) infection is associated with chronic lung disease and impaired pulmonary function; however, longitudinal pulmonary function phenotypes in HIV are undefined. Objectives: To identify pulmonary function trajectories, their determinants, and outcomes. Methods: We used data from participants with HIV in the Pittsburgh HIV Lung Cohort with three or more pulmonary function tests between 2007 and 2020. We analyzed post-bronchodilator forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), and FEV1/FVC, and diffusing capacity of the lung for carbon monoxide (DlCO) using group-based trajectory modeling to identify subgroups of individuals whose measurements followed a similar pattern over time. We examined the association between participant characteristics and trajectories using multivariable logistic regression. In exploratory adjusted analyses restricted to individuals with available plasma cytokine data, we investigated the association between 18 individual standardized cytokine concentrations and trajectories. We compared mortality, dyspnea prevalence, respiratory health status, and 6-minute-walk distance between phenotypes. Results: A total of 265 participants contributed 1,606 pulmonary function measurements over a median follow-up of 8.1 years. We identified two trajectories each for FEV1 and FVC: "low baseline, slow decline" and "high baseline, rapid decline." There were three trajectory groups for FEV1/FVC: "rapid decline," "moderate decline," and "slow decline." Finally, we identified two trajectories for DlCO: "baseline low" and "baseline high." The low baseline, slow decline FEV1 and FVC, rapid decline, and moderate decline FEV1/FVC, and baseline low DlCO phenotypes were associated with increased dyspnea prevalence, worse respiratory health status, and decreased 6-minute-walk distance. The baseline low DlCO phenotype was also associated with worse mortality. Current smoking and pack-years of smoking were associated with the adverse FEV1, FEV1/FVC, and DlCO phenotypes. Detectable viremia was the only HIV marker associated with the adverse DlCO phenotype. C-reactive protein and endothelin-1 were associated with the adverse FEV1 and FVC phenotypes, and endothelin-1 trended toward an association with the adverse DlCO phenotype. Conclusions: We identified novel, distinct longitudinal pulmonary function phenotypes with significant differences in characteristics and outcomes. These findings highlight the importance of lung dysfunction over time in people with HIV and should be validated in additional cohorts.