Characterization of biological variation of peripheral blood immune cytome in an Indian cohort

Abstract

Immune parameters show characteristic normal baseline levels and variance in the population. We characterised the degree of inter-individual and within-individual variation over one-year time period in 33 immune cell subsets by flow cytometry in peripheral blood mononuclear cells from 43 healthy young adult volunteers. Our analysis revealed that immune subsets that showed low variability between individuals also showed low short-term fluctuations within-individuals, as well as concordance in siblings. However, when baseline levels and degree of fluctuation were considered together, individuals failed to cluster into discreet groups. Together, the data reveal complex inter-relationships between immune subsets in individuals, and provide insights into the observed heterogeneity between individuals and between multiple immune subsets.

A dynamic COVID-19 immune signature includes associations with poor prognosis

“…As reported for other healthy cohorts 34 , HC monocyte numbers displayed a high coefficient of variation, but nonetheless their counts trended downward in COVID-19 versus upward in LRTI (Extended Data Fig. 4b), and their composition changed, with depletions of classical monocytes versus increased frequencies of CD16 + CD14 + intermediate monocytes (Extended Data Fig.…”

A consensus Covid-19 immune signature combines immuno-protection with discrete sepsis-like traits associated with poor prognosis

“…To investigate further the interplay of innate immune cells and cytokines in CP blood, we examined monocytes. As has been reported for healthy individuals 43 , the CV for HC monocytes was high, but a tendency of reduced numbers was still evident in CP ( Fig 4a ). Monocyte composition also changed, particularly with increased representation of CD16 + CD14 + intermediate monocytes (MO IM ) ( Fig 4a; Supp Fig 3d-f ), as was reported for responses to virus infection 44,45 .…”

New approach to determine the healthy immune variations by combining clustering methods

“…Through a robust clustering methodology including three complementary approaches, we observed that the leukocyte subsets were organized as a continuum and we replicated these observations in an independent cohort. This absence of clusters of individuals sharing similar variation of immune cell composition is aligned with recent findings 12 , 13 . Likewise, the homogenous blood cell composition observed in our cohorts reflects a balanced homeostasis expected in healthy subjects.…”

“…We therefore cannot exclude that the addition of other leukocyte subsets unveils clusters. However, it should be noted that others research teams did not find clusters despite the use of such additional leukocyte subsets 12 , 13 . Thirdly, a significant part of the overall variability could be explained by the genetic makeup of individuals 9 , 26 , 35 and the influence of microbiota 25 , 36 , but these factors were not available in this study.…”

“…Defining the limits of a healthy immune system is therefore a prior step to capture variability in disease conditions and several healthy cohorts have been published in this perspective 7 – 10 . While many studies have investigated the inter-individual variability for each immune cell subsets separately, few have profiled the global immune cell composition and their interdependence in healthy cohorts 11 – 13 . The clustering methods described in the medical literature 11 , 12 to capture this immune cell interdependence were mainly based on traditional K-means algorithm which lacks of robustness face to outliers and noise 14 .…”