Multi-Cellular Immunological Interactions Associated With COVID-19 Infections - Verma, Jitender S.; Libertin, Claudia R.; Gupta, Yash; Khanna, Geetika; Kumar, Rohit; Arora, Balvinder S.; Krishna, Loveneesh; Fasina, Folorunso O.; Hittner, James B.; Antoniades, Athos; van Regenmortel, Marc H. V.; Durvasula, Ravi; et al. (Frontiers in Immunology, 2022)
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 (145 individuals, 384 temporal observations). Within hospital (<90-day) death or discharge were retrospectively predicted in reference to 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. Construct validity was documented because more or novel information was generated by the non-reductionist than the reductionist method. Internal validity was supported: several co-morbidities did not seem to prevent discrimination. External validity (generalizability) was strongly suggested: two populations located in different continents reported, since their first test, similar (although not identical) findings. The assessment of statistical validity demonstrated that the non-reductionist method could complement statistical analyses. The non-reductionist method also promoted research. Because survivors and non-survivors of both populations were infected by the same pathogen (and variant), outcomes were not likely to be exclusively explained by the pathogen. It is then suggested that future studies may consider whether immunological differences between survivors and non-survivors precede infection. While multi-cellular interactions seem to be rapidly uncovered, no complex or straightforward indicator is likely to apply to all conditions. To promote discrimination and hypothesis generation, multiple data structures are recommended.