Diana van den Heuvel1, Michelle A E Jansen2, Kazem Nasserinejad3, Willem A Dik1, Ellen G van Lochem1, Liesbeth E Bakker-Jonges1, Halima Bouallouch-Charif1, Vincent W V Jaddoe4, Herbert Hooijkaas1, Jacques J M van Dongen1, Henriëtte A Moll5, Menno C van Zelm6. 1. Department of Immunology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. 2. Generation R Study Group, Erasmus MC, University Medical Center, Rotterdam, The Netherlands; Department of Pediatrics, Erasmus MC-Sophia, Rotterdam, The Netherlands. 3. Department of Biostatistics, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. 4. Generation R Study Group, Erasmus MC, University Medical Center, Rotterdam, The Netherlands; Department of Pediatrics, Erasmus MC-Sophia, Rotterdam, The Netherlands; Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. 5. Department of Pediatrics, Erasmus MC-Sophia, Rotterdam, The Netherlands. 6. Department of Immunology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands; Department of Immunology and Pathology, Central Clinical School, Monash University, Melbourne, Australia. Electronic address: menno.vanzelm@monash.edu.
Abstract
BACKGROUND: Numbers of blood leukocyte subsets are highly dynamic in childhood and differ greatly between subjects. Interindividual variation is only partly accounted for by genetic factors. OBJECTIVE: We sought to determine which nongenetic factors affect the dynamics of innate leukocytes and naive and memory lymphocyte subsets. METHODS: We performed 6-color flow cytometry and linear mixed-effects modeling to define the dynamics of 62 leukocyte subsets from birth to 6 years of age in 1182 children, with 1 to 5 measurements per subject. Subsequently, we defined the effect of prenatal maternal lifestyle-related or immune-mediated determinants, birth characteristics, and bacterial/viral exposure-related determinants on leukocyte subset dynamics. RESULTS: Functionally similar leukocyte populations were grouped by using unbiased hierarchical clustering of patterns of age-related leukocyte dynamics. Innate leukocyte numbers were high at birth and predominantly affected by maternal low education level. Naive lymphocyte counts peaked around 1 year, whereas most memory lymphocyte subsets more gradually increased during the first 4 years of life. Dynamics of CD4+ T cells were predominantly associated with sex, birth characteristics, and persistent infections with cytomegalovirus (CMV) or EBV. CD8+ T cells were predominantly associated with CMV and EBV infections, and T-cell receptor γδ+ T cells were predominantly associated with premature rupture of membranes and CMV infection. B-cell subsets were predominantly associated with sex, breast-feeding, and Helicobacter pylori carriership. CONCLUSIONS: Our study identifies specific dynamic patterns of leukocyte subset numbers, as well as nongenetic determinants that affect these patterns, thereby providing new insights into the shaping of the childhood immune system.
BACKGROUND: Numbers of blood leukocyte subsets are highly dynamic in childhood and differ greatly between subjects. Interindividual variation is only partly accounted for by genetic factors. OBJECTIVE: We sought to determine which nongenetic factors affect the dynamics of innate leukocytes and naive and memory lymphocyte subsets. METHODS: We performed 6-color flow cytometry and linear mixed-effects modeling to define the dynamics of 62 leukocyte subsets from birth to 6 years of age in 1182 children, with 1 to 5 measurements per subject. Subsequently, we defined the effect of prenatal maternal lifestyle-related or immune-mediated determinants, birth characteristics, and bacterial/viral exposure-related determinants on leukocyte subset dynamics. RESULTS: Functionally similar leukocyte populations were grouped by using unbiased hierarchical clustering of patterns of age-related leukocyte dynamics. Innate leukocyte numbers were high at birth and predominantly affected by maternal low education level. Naive lymphocyte counts peaked around 1 year, whereas most memory lymphocyte subsets more gradually increased during the first 4 years of life. Dynamics of CD4+ T cells were predominantly associated with sex, birth characteristics, and persistent infections with cytomegalovirus (CMV) or EBV. CD8+ T cells were predominantly associated with CMV and EBV infections, and T-cell receptor γδ+ T cells were predominantly associated with premature rupture of membranes and CMV infection. B-cell subsets were predominantly associated with sex, breast-feeding, and Helicobacter pylori carriership. CONCLUSIONS: Our study identifies specific dynamic patterns of leukocyte subset numbers, as well as nongenetic determinants that affect these patterns, thereby providing new insights into the shaping of the childhood immune system.
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