Association of gut microbial dysbiosis with disease severity, response to therapy and disease outcomes in Indian patients with COVID-19

Abstract Background Severe coronavirus disease 2019 (COVID-19) is associated with systemic hyper-inflammation. An adaptive interaction between gut microbiota and host immune systems is important for intestinal homeostasis and systemic immune regulation. The association of gut microbial composition and functions with COVID-19 disease severity is sparse, especially in India. We analysed faecal microbial diversity and abundances in a cohort of Indian COVID-19 patients to identify key signatures in the gut microbial ecology in patients with severe COVID-19 disease as well as in response to different therapies. The composition of the gut microbiome was characterized using 16Sr RNA gene sequences of genomic DNA extracted from faecal samples of 52 COVID-19 patients. Metabolic pathways across the groups were predicted using PICRUSt2. All statistical analyses were done using Vegan in the R environment. Plasma cytokine abundance at recruitment was measured in a multiplex assay. Results The gut microbiome composition of mild and severe patients was found to be significantly different. Immunomodulatory commensals, viz. Lachnospiraceae family members and Bifidobacteria producing butyrate and short-chain fatty acids (SCFAs), were under represented in patients with severe COVID-19, with an increased abundance of opportunistic pathogens like Eggerthella. The higher abundance of Lachnoclostridium in severe disease was reduced in response to convalescent plasma therapy. Specific microbial genera showed distinctive trends in enriched metabolic pathways, strong correlations with blood plasma cytokine levels, and associative link to disease outcomes. Conclusion Our study indicates that, along with SARS-CoV-2, a dysbiotic gut microbial community may also play an important role in COVID-19 severity through modulation of host immune responses

Circulating Interleukin-8 Dynamics Parallels Disease Course and Is Linked to Clinical Outcomes in Severe COVID-19

Severe COVID-19 frequently features a systemic deluge of cytokines. Circulating cytokines that can stratify risks are useful for more effective triage and management. Here, we ran a machine-learning algorithm on a dataset of 36 plasma cytokines in a cohort of severe COVID-19 to identify cytokine/s useful for describing the dynamic clinical state in multiple regression analysis. We performed RNA-sequencing of circulating blood cells collected at different time-points. From a Bayesian Information Criterion analysis, a combination of interleukin-8 (IL-8), Eotaxin, and Interferon-γ (IFNγ) was found to be significantly linked to blood oxygenation over seven days. Individually testing the cytokines in receiver operator characteristics analyses identified IL-8 as a strong stratifier for clinical outcomes. Circulating IL-8 dynamics paralleled disease course. We also revealed key transitions in immune transcriptome in patients stratified for circulating IL-8 at three time-points. The study identifies plasma IL-8 as a key pathogenic cytokine linking systemic hyper-inflammation to the clinical outcomes in COVID-19

Clinical Trial Subgroup Analyses to Investigate Clinical and Immunological Outcomes of Convalescent Plasma Therapy in Severe COVID-19

Objective: To assess the clinical and immunological benefits of passive immunization using convalescent plasma therapy (CPT). Materials and Methods: A series of subclass analyses were performed on the previously published outcome data and accompanying clinical metadata from a completed randomized controlled trial (RCT) (Clinical Trial Registry of India, number CTRI/2020/05/025209). The subclass analyses were performed on the outcome data and accompanying clinical metadata from a completed RCT (patient recruitment between May 15, 2020 and October 31, 2020). Data on the plasma abundance of a large panel of cytokines from the same cohort of patients were also used to characterize the heterogeneity of the putative anti-inflammatory function of convalescent plasma (CP) in addition to passively providing neutralizing antibodies. Results: Although the primary clinical outcomes were not significantly different in the RCT across all age groups, significant immediate mitigation of hypoxia, reduction in hospital stay, and significant survival benefit were registered in younger (<67 years in our cohort) patients with severe coronavirus disease 2019 and acute respiratory distress syndrome on receiving CPT. In addition to neutralizing the antibody content of CP, its anti-inflammatory proteome, by attenuation of the systemic cytokine deluge, significantly contributed to the clinical benefits of CPT. Conclusion: Subgroup analyses revealed that clinical benefits of CPT in severe coronavirus disease 2019 are linked to the anti-inflammatory protein content of CP apart from the anti–severe acute respiratory syndrome coronavirus 2 neutralizing antibody content

Development and Validation of a Treatment Benefit Index to Identify Hospitalized Patients With COVID-19 Who May Benefit From Convalescent Plasma

Importance: Identifying which patients with COVID-19 are likely to benefit from COVID-19 convalescent plasma (CCP) treatment may have a large public health impact.   Objective: To develop an index for predicting the expected relative treatment benefit from CCP compared with treatment without CCP for patients hospitalized for COVID-19 using patients' baseline characteristics.   Design, Setting, and Participants: This prognostic study used data from the COMPILE study, ie, a meta-analysis of pooled individual patient data from 8 randomized clinical trials (RCTs) evaluating CCP vs control in adults hospitalized for COVID-19 who were not receiving mechanical ventilation at randomization. A combination of baseline characteristics, termed the treatment benefit index (TBI), was developed based on 2287 patients in COMPILE using a proportional odds model, with baseline characteristics selected via cross-validation. The TBI was externally validated on 4 external data sets: the Expanded Access Program (1896 participants), a study conducted under Emergency Use Authorization (210 participants), and 2 RCTs (with 80 and 309 participants).   Exposure: Receipt of CCP.   Main Outcomes and Measures: World Health Organization (WHO) 11-point ordinal COVID-19 clinical status scale and 2 derivatives of it (ie, WHO score of 7-10, indicating mechanical ventilation to death, and WHO score of 10, indicating death) at day 14 and day 28 after randomization. Day 14 WHO 11-point ordinal scale was used as the primary outcome to develop the TBI.   Results: A total of 2287 patients were included in the derivation cohort, with a mean (SD) age of 60.3 (15.2) years and 815 (35.6%) women. The TBI provided a continuous gradation of benefit, and, for clinical utility, it was operationalized into groups of expected large clinical benefit (B1; 629 participants in the derivation cohort [27.5%]), moderate benefit (B2; 953 [41.7%]), and potential harm or no benefit (B3; 705 [30.8%]). Patients with preexisting conditions (diabetes, cardiovascular and pulmonary diseases), with blood type A or AB, and at an early COVID-19 stage (low baseline WHO scores) were expected to benefit most, while those without preexisting conditions and at more advanced stages of COVID-19 could potentially be harmed. In the derivation cohort, odds ratios for worse outcome, where smaller odds ratios indicate larger benefit from CCP, were 0.69 (95% credible interval [CrI], 0.48-1.06) for B1, 0.82 (95% CrI, 0.61-1.11) for B2, and 1.58 (95% CrI, 1.14-2.17) for B3. Testing on 4 external datasets supported the validation of the derived TBIs.   Conclusions and Relevance: The findings of this study suggest that the CCP TBI is a simple tool that can quantify the relative benefit from CCP treatment for an individual patient hospitalized with COVID-19 that can be used to guide treatment recommendations. The TBI precision medicine approach could be especially helpful in a pandemic

Post COVID sequelae among COVID-19 survivors: insights from the Indian National Clinical Registry for COVID-19

Introduction The effects of COVID-19 infection persist beyond the active phase. Comprehensive description and analysis of the post COVID sequelae in various population groups are critical to minimise the long-term morbidity and mortality associated with COVID-19. This analysis was conducted with an objective to estimate the frequency of post COVID sequelae and subsequently, design a framework for holistic management of post COVID morbidities.Methods Follow-up data collected as part of a registry-based observational study in 31 hospitals across India since September 2020–October 2022 were used for analysis. All consenting hospitalised patients with COVID-19 are telephonically followed up for up to 1 year post-discharge, using a prestructured form focused on symptom reporting.Results Dyspnoea, fatigue and mental health issues were reported among 18.6%, 10.5% and 9.3% of the 8042 participants at first follow-up of 30–60 days post-discharge, respectively, which reduced to 11.9%, 6.6% and 9%, respectively, at 1-year follow-up in 2192 participants. Patients who died within 90 days post-discharge were significantly older (adjusted OR (aOR): 1.02, 95% CI: 1.01, 1.03), with at least one comorbidity (aOR: 1.76, 95% CI: 1.31, 2.35), and a higher proportion had required intensive care unit admission during the initial hospitalisation due to COVID-19 (aOR: 1.49, 95% CI: 1.08, 2.06) and were discharged at WHO ordinal scale 6–7 (aOR: 49.13 95% CI: 25.43, 94.92). Anti-SARS-CoV-2 vaccination (at least one dose) was protective against such post-discharge mortality (aOR: 0.19, 95% CI: 0.01, 0.03).Conclusion Hospitalised patients with COVID-19 experience a variety of long-term sequelae after discharge from hospitals which persists although in reduced proportions until 12 months post-discharge. Developing a holistic management framework with engagement of care outreach workers as well as teleconsultation is a way forward in effective management of post COVID morbidities as well as reducing mortality