TY - JOUR
T1 - Age-Dependent Normalization Functions for T Lymphocytes in Healthy Individuals
AU - EPIICAL consortium
AU - Schröter, Juliane
AU - Borghans, José A M
AU - Bitter, W Marieke
AU - van Dongen, Jacques J M
AU - de Boer, Rob J
N1 - Publisher Copyright:
©2023 by TheAmericanAssociation of Immunologists, Inc.
PY - 2023/6/15
Y1 - 2023/6/15
N2 - Lymphocyte numbers naturally change through age. Normalization functions to account for this are sparse and mostly disregard measurements from children in which these changes are most prominent. In this study, we analyze cross-sectional numbers of mainly T lymphocytes (CD3+, CD3+CD4+, and CD3+CD8+) and their subpopulations (naive and memory) from 673 healthy Dutch individuals ranging from infancy to adulthood (0-62 y). We fitted the data by a delayed exponential function and estimated parameters for each lymphocyte subset. Our modeling approach follows general laboratory measurement procedures in which absolute cell counts of T lymphocyte subsets are calculated from observed percentages within a reference population that is truly counted (typically the total lymphocyte count). Consequently, we obtain one set of parameter estimates per T cell subset representing both the trajectories of their counts and percentages. We allow for an initial time delay of half a year before the total lymphocyte counts per microliter of blood start to change exponentially, and we find that T lymphocyte trajectories tend to increase during the first half a year of life. Thus, our study provides functions describing the general trajectories of T lymphocyte counts and percentages of the Dutch population. These functions provide important references to study T lymphocyte dynamics in disease, and they allow one to quantify losses and gains in longitudinal data, such as the CD4+ T cell decline in HIV-infected children and/or the rate of T cell recovery after the onset of treatment.
AB - Lymphocyte numbers naturally change through age. Normalization functions to account for this are sparse and mostly disregard measurements from children in which these changes are most prominent. In this study, we analyze cross-sectional numbers of mainly T lymphocytes (CD3+, CD3+CD4+, and CD3+CD8+) and their subpopulations (naive and memory) from 673 healthy Dutch individuals ranging from infancy to adulthood (0-62 y). We fitted the data by a delayed exponential function and estimated parameters for each lymphocyte subset. Our modeling approach follows general laboratory measurement procedures in which absolute cell counts of T lymphocyte subsets are calculated from observed percentages within a reference population that is truly counted (typically the total lymphocyte count). Consequently, we obtain one set of parameter estimates per T cell subset representing both the trajectories of their counts and percentages. We allow for an initial time delay of half a year before the total lymphocyte counts per microliter of blood start to change exponentially, and we find that T lymphocyte trajectories tend to increase during the first half a year of life. Thus, our study provides functions describing the general trajectories of T lymphocyte counts and percentages of the Dutch population. These functions provide important references to study T lymphocyte dynamics in disease, and they allow one to quantify losses and gains in longitudinal data, such as the CD4+ T cell decline in HIV-infected children and/or the rate of T cell recovery after the onset of treatment.
KW - Child
KW - Humans
KW - Cross-Sectional Studies
KW - T-Lymphocyte Subsets
KW - Lymphocyte Subsets
KW - CD4-Positive T-Lymphocytes
KW - Lymphocyte Count
UR - http://www.scopus.com/inward/record.url?scp=85163231215&partnerID=8YFLogxK
U2 - 10.4049/jimmunol.2200520
DO - 10.4049/jimmunol.2200520
M3 - Article
C2 - 37125851
SN - 0022-1767
VL - 210
SP - 1882
EP - 1888
JO - The Journal of Immunology
JF - The Journal of Immunology
IS - 12
ER -