Multi-Cellular Immunological Interactions Associated With COVID-19 Infections

Abstract

To rapidly prognosticate and generate hypotheses on pathogenesis, leukocyte multi-cellularity was evaluated in SARS-CoV-2 infected patients treated in India or the United States (152 individuals, 384 temporal observations). Within hospital (<90-day) death or discharge were retrospectively predicted based on the admission complete blood cell counts (CBC). Two methods were applied: (i) a “reductionist” one, which analyzes each cell type separately, and (ii) a “non-reductionist” method, which estimates multi-cellularity. The second approach uses a proprietary software package that detects distinct data patterns generated by complex and hypothetical indicators and reveals each data pattern’s immunological content and associated outcome(s). In the Indian population, the analysis of isolated cell types did not separate survivors from non-survivors. In contrast, multi-cellular data patterns differentiated six groups of patients, including, in two groups, 95.5% of all survivors. Some data structures revealed one data point-wide line of observations, which informed at a personalized level and identified 97.8% of all non-survivors. Discovery was also fostered: some non-survivors were characterized by low monocyte/lymphocyte ratio levels. When both populations were analyzed with the non-reductionist method, they displayed results that suggested survivors and non-survivors differed immunologically as early as hospitalization day 1.

Clinical and laboratory profiles of the SARS-CoV-2 Delta variant compared with pre-Delta variants

“…Other similar markers in both Wave 1 and Wave 2 included lymphopenia and elevations of procalcitonin, IL-6, d -dimer, and platelet count. Other studies have also indicated that absolute lymphopenia is not a predictor of outcomes by itself ( Verma et al, 2022 ). These indicators remain elevated in severe COVID-19 but do not differ between the waves ( Lopez-Castaneda et al, 2021 ;Malik et al, 2021 ).…”

Decoding Immuno-Competence: A Novel Analysis of Complete Blood Cell Count Data in COVID-19 Outcomes

“…To measure personalized immune dynamics and to extract hidden patterns, the assessment of immunological complexity has been recommended [24][25][26]. To explore complexity, interactions involving two or more biological elements-such as lymphocytes and monocytes-may describe biological functions that influence outcomes [27]. Such complex functions change over time and may exhibit feedforward and feedback loops [9,28].…”

“…The previous considerations may influence the way immuno-competence is explored. In several clinical entities (e.g., COVID-19, sepsis, hantavirus), the early disease stage is not always associated with death [27,[37][38][39][40].…”

“…Discharge was based on negative testing and the alleviation of life-threatening conditions. Individuals treated for immunosuppression, malignancy, pregnancy and/or hospitalized for at least three weeks in the previous six months were excluded [27]. The outcome (survival or no survival) was determined at 30 days after hospitalization.…”

Mycolactone: A Broad Spectrum Multitarget Antiviral Active in the Picomolar Range for COVID-19 Prevention and Cure

“…Clinicians are overwhelmed by a complete change in viral symptoms every time there is a new strain in circulation [ 3 , 4 ]. Mathematical modeling has been helpful to only an extent [ 5 , 6 ], even with a much more extensive understanding of risk factors and prognosis [ 7 , 8 ]. Our group has shown the usefulness of heparin as a viral fusion inhibitor by targeting spike protein early on in the pandemic [ 9 ].…”