Rhythmic profile of memory T and B-cells along childhood and adolescence

Immunobiography describes the life-long effects of exogenous or endogenous stimuli on remodeling of immune cell biology, including the development of memory T and B-cells. The present study aimed at investigating the rhythms of changes in phenotypic features of memory T and B-cells along childhood and adolescence. A descriptive-observational investigation was conducted including 812 healthy volunteers, clustered into six consecutive age groups (9Mths–1Yr; 2Yrs; 3–4Yrs; 5–7Yrs; 8–10Yrs; 11–18Yrs). Immunophenotypic analysis of memory T-cell (CD4+ and CD8+) and B-cell subsets were performed by flow cytometry. The results pointed out that memory-related biomarkers of T and B-cells displayed a bimodal profile along healthy childhood and adolescence, regardless of sex. The first stage of changes occurs around 2Yrs, with predominance of naive cells, while the second and more prominent wave occurs around the age 8–10Yrs, with the prevalence of memory phenotypes. The neighborhood connectivity profile analysis demonstrated that the number of correlations reaches a peak at 11–18Yrs and lower values along the childhood. Males presented higher and conserved number of correlations when compared to females. Altogether, our results provide new insights into immunobiography and a better understanding of interactions among the cellular subsets studied here during childhood and adolescence.


Rhythmic profile of memory T and B-cells along childhood and adolescence according to sex
The dynamic of changes in memory-related phenotypes was further assessed in males and females at distinct ages along childhood and adolescence (Fig. 2).Comparative analysis between males and females at matching age ranges revealed significant differences only for NCD4 at 8-10 Yrs and for eEFCD8 at 11-18 Yrs (Fig. 2, # symbols).These findings demonstrated that the analysis of rhythmic profile along adjacent ages represent a more . Rhythmic profile of memory T and B-cells along childhood and adolescence.The overall profile of memory T-cell subsets (CD4 + and CD8 + ) and B-cells was characterized in peripheral blood samples from healthy children and adolescents (ALL (Green color bar), n = 812), categorized into distinct age groups (9 Mths -1 Yr , n = 135; 2 Yrs , n = 147; 3-4 Yrs , n = 129; 5-7 Yrs , n = 133; 8-10 Yrs , n = 140 and 11-18 Yrs , n = 128).Immunophenotypic analysis of NAIVE (N), Early EFFECTOR (eEF), CENTRAL (CM) and EFFECTOR MEMORY (EM) T-cell subsets as well as NAIVE (N), Early EFFECTOR (eEF), NON-CLASSICAL MEMORY (nCM) and CLASSICAL MEMORY (CM) B-cells was carried out by flow cytometry as described in Material and Methods.The results are shown as scattering distribution of individual data of relative frequency of gated cells (% within CD4 + , CD8 + or CD19 + gated cells) over bars of median values for each age range.Comparative analysis between pairs of adjacent age groups was carried out by Mann-Whitney test and significant differences at p < 0.05 underscored by connecting lines for comparisons with the immediately earlier age range and the statistical significance identified by *, **, ***, and **** for p values ≤ 0.05; ≤ 0.01, ≤ 0.001, and ≤ 0.0001, respectively.), a decrease in several memory-related biomarkers was also identified in males (NCD8, NCD19, eEFCD19, CMCD4, CMCD8, and EMCD8) and in females (NCD4, NCD19, eEFCD19, and EMCD8), along with the increases in eEFCD4, eEFCD8 and CMCD19 observed in both sexes (Fig. 2).
Similar to the data observed for the general population (ALL), the rhythmic changes observed for males and females followed a bimodal profile with a first peak around age 2 Yrs and a second and more prominent crest observed at age 8-10 Yrs (Fig. 2).

Predicted probability of changes in memory T and B-cells along healthy childhood and adolescence
Predicted probabilities were calculated by logistic regression to assess the strength of association between memory T and B-cell subsets with ageing during childhood and adolescence (Fig. 3).The predicted probabilities of subjects to present a given phenotype of memory T or B-cell subset in high frequency were estimated according to age continuum (months) with further data stratification by sex.Data analysis showed that naive T and B-cells (NCD4, NCD8, NCD19) had a continuous decrease in values along healthy childhood and adolescence.Conversely, memory T-cell subsets (eEFCD4; eEFCD8, CMCD4, CMCD8, EMCD4, and EMCD8) showed a continuous increase in values of predict probability along healthy childhood and adolescence.While a progressive decrease in NCD19 and an increase of CMCD19 was observed for ALL group, no differences were observed when the study population was segregated by sex.No difference in eEFCD19 and nCMCD19 were observed (Fig. 3).

Panoramic signatures of memory T and B-cells along childhood and adolescence
Aiming at providing a panoramic snapshot of memory T-cell (CD4 + and CD8 + ) and B-cell subsets along healthy childhood and adolescence, the original results expressed as continuous variables were converted into categorical data to estimate the proportion of subjects with values above the global median cut-off defined for each memory cell subset (Fig. 4).
NCD4, NCD8 and CMCD19 phenotypes were observed in high proportion of subjects at age 9 Mths -1 Yr .While NCD4 and NCD8 still remained elevated at age 2 Yrs , an increased proportion of subjects also presented elevated levels of NCD19, eEFCD19, and nCMCD19 by the age of 2 Yrs .Around age 3-4 Yrs , a selective increase in the naive cell subsets (NCD4, NCD8, and NCD19) was still observed.Inversely, at age 5-7 Yrs , eEFCD4, eEFCD8, CMCD4, EMCD4, and EMCD8 cells increased, which highlight them as relevant memory-related biomarkers, along with NCD19.Thereafter at age 8-10 Yrs , the set of memory-related phenotypes observed expanded with the inclusion of eEFCD19 and CMCD8 at age 5-7 Yrs .
Aiming at providing a complementary landscape profile of changes in the overall signature of memory T and B-cells, heatmaps were assembled to underscore the cell phenotypes with increased proportion at each age range (Fig. 4B).The heatmap profiles pointed out the existence of a clear dichotomic profile among memory T-cell subsets.At early age there was a predominance of naive T-cell subsets (NCD4 and NCD8) and a shift towards memory-related phenotypes (eEFCD4, eEFCD8, EMCD4, EMCD8, CMCD4 and CMCD8), with marked expansion at late childhood (8-10 Yrs ) with slight remodeling at adolescence (11)(12)(13)(14)(15)(16)(17)(18) ).Conversely, the signature of memory B-cell phenotypes exhibited a distinct rhythm.While NCD19 displayed a unimodal peak at 3-4 Yrs and 5-7 Yrs , CMCD19 exhibited an opposite profile with higher values at 9 Mths -1 Yr and 11-18 Yrs .Moreover, the unimodal peak of nCMCD19 at age 2 Yrs contrasted with the bimodal profile of eEFCD19 with waves at 2 Yrs and 8-10 Yrs (Fig. 4B).
The analysis of signature patterns of memory T and B-cells according to sex was also performed (Fig. 5).Data analysis demonstrated that similarly to what was observed for the general population (ALL), higher proportion of males and females presented elevated levels of naive cell subsets at early ages with an increase of memory cell subsets at late age groups (Fig. 5A).Heatmap analysis further corroborated these findings, demonstrating that naive cell subsets were predominant at early childhood and memory phenotypes at late age groups (Fig. 5B).

Integrative networks of memory T and B-cells along healthy childhood and adolescence
Integrative network analysis was performed to estimate the neighborhood connectivity profile between memory T-cell subsets and B-cells along childhood and adolescence (Fig. 6).The networks were constructed based on the correlation analysis between values of memory T and B-cell subsets obtained at each age range.The number of age-selective/total correlations were lower at childhood (9 Mths -1 Yr = 6/32; 2 Yrs = 4/35; 3-4 Yrs = 0/26; 5-7 Yrs = 6/37 and 8-10 Yrs = 3/34), reaching higher values at 11-18 Yrs (14/44) (Fig. 6).The analysis of common correlations along all age groups identified a set of 19 conserved axis, integrating naive cells, memory T and B-cell subsets (Supplementary Fig. 2).

Discussion
There are several pieces of evidence that point out for the development and the ageing processes as non-linear events influencing the immune system, with changes occurring with distinct magnitudes and rhythms in childhood, adolescence, adulthood, and advanced ages.These changes are characterized by waves and are reflected in the production of soluble mediators, such as IL-1β, IL-12, IL-15, IL-7 and IL-2, as well as in the composition of memory T and B cell subsets 5,[10][11][12][13] .Ageing begins in the moment we start to live and we can consider that the development process at childhood and adolescence is part of it.In this sense, combining the scientific knowledge on the changes that occur in the immune system during childhood, with those occurring in later ages, can provide insights for the understanding of the ageing process throughout lifetime.During childhood, the immune system gradually matures due to the exposure to infections and vaccinations.As a result of these challenges, the individual develops an expanding repertoire of specific memory immune cells that guarantees long standing protection 2 .Aiming at providing a better   comprehension of the changes in the immune system regarding cellularity and of the rhythms in which they occur, the present study investigated the proportion of T and B-cell subsets during childhood and adolescence.
In general, changes in the percentages of T and B-cells were observed during childhood.Memory T-cells expand throughout childhood and adolescence, while the naïve cell compartment contracts.This pattern is similar for CD4 + and CD8 + T-cells as well as B-cells.In agreement, previous studies have reported similar overall shift of naïve T and B-cells to mature cells as we age 5,13 .This phenomenon could be characterized as a development of a robust immune response after multiple exposure to external challenges.It is important to mention that differences were observed between the rhythms of memory T and B-cells along childhood development.While there was a clear association between the changes in all memory T-cell subsets with age continuous, our findings demonstrated that only NCD19 and CMCD19 B-cells presented an association with age continuum along childhood development.Amongst B-cell subsets, our data demonstrated a peak of naïve cells around 3-4 Yrs and 5-8 Yrs , contrasting with classical memory, which presented higher values at 9 Mths -1 Yr and 11-18 Yrs .The analysis of predicted probability along age continuum demonstrated an opposite profile between the progressive waning of NCD19 and increasing frequency of CMCD19.Previous reports by Schatorjé et al. 14 and Duchamp et al., 15 , carried out in non-endemic areas for parasitic/infectious diseases, demonstrated a progressive decline in naïve   B-cells (CD27 -IgD + ) and an increase of memory B-cells (CD27 + IgD -) along childhood development.As the age ranges included in our study differ from those employed by Schatorjé et al. 14 and Duchamp et al. 15 , our results could not be directly compared with their previous reports.However, our findings of predicted probability corroborated the rhythm of B-cell subsets identified by them during childhood development 14,15 .Besides the differences in the age ranges employed in our study, other factors that may account for the discrepancies would be the intrinsic factors associated with the immunobiography of the study populations living in endemic and non-endemic areas for parasitic/infectious diseases.During childhood, the changes in the lymphocyte compartment and the relative percentage of memory B-cells over time reflect the infant exposure to antigenic stimuli during parasitic/infectious diseases.Depending on the pathogen, distinct memory B-cells are developed, which constitutes a target for pathogen-induced subversion.This may lead to altered memory B-cell phenotypes 16 .
Another point that should be considered is that infants have significantly higher numbers of peripheral CD19 + B cells as compared to adults, and unlike T-cells, the B-cell compartment displays a distinct scattering profile along age ranges.While the frequencies of T-cells show a more homogeneous distribution between minimum and maximum values within a given age range (2.7 times difference), a broader variation (23 times difference) is observed for B-cells among subjects within each age range 17 .Together, these phenomena may explain the apparent divergent rhythms of memory T and B-cells along during childhood development reported amongst studies carried out in endemic and non-endemic areas for parasitic/infectious diseases.Some of the memory CD4 + and CD8 + T and B-lymphocyte subsets showed high connectivity in all age groups (overall study population, males, and females).In this sense, NCD4 + and CMCD4 + seemed to interact more frequently with other cell subsets.These results suggest that these cells play an important role when the immune system is challenged.CMCD4 + are restricted to blood and lymphoid organs, however, they provide an adaptive www.nature.com/scientificreports/protection through multiple pathways 18 .This protective response is influenced by the challenges occurring in the external milieu such as infections or vaccination 18 .The increased NCD4 + phenotype may be associated with the age of the individuals since during childhood and adolescence they undergo a period of complex immunity development.Thus, naive cells are recruited and, thus, undergo differentiation into memory phenotypes to build a robust immune system.
Our study suggests that normal development during childhood does not only depend upon changes in memory T and B-cell subsets, but cell-to-cell interaction.We demonstrated that by calculating their connectivity during development.The neighborhood connectivity and predicted probabilities had specific periods when changes can be identified.Around the age of 10 years, a broad increase of connectivity, in addition to an increased probability of find mature memory cells (eEFCD4 + , eEFCD8 + , CMCD4 + , CMCD8 + , EFCD4 + , and EFCD8 + ) were observed, regardless of sex.These alterations could be associated to an endocrine event named gonadarche.The gonadarche consist in the pubertal reactivation of the hypothalamic-pituitary-gonadal axis, which results in development of gonads and posterior sexual development 19 .The average age of onset of this event in females is approximately 10 years of age, while in males this event occurs around 11 years of age [20][21][22] .In spite of these relevant findings, it is important to mention that changes in the connectivity based on correlation analysis do not necessarily result or reflect on changes in biological connections and pathways and further studies are yet required to better understand the relationship between these findings and changes in cellular functions.
Sexual hormones can influence the immune responses by binding nuclear receptors or membrane-bound receptors that initiate signal transduction pathways in immune cells 8,23,24 .Both innate and adaptive immune cells express hormone receptors as reported in hematopoietic stem cells, natural killer cells, plasmacytoid dendritic cells and monocytes as well as T and B-lymphocytes 23,24 .Thompson and colleagues 25 have reported that adolescents, both males and females, presented significant changes in the proportion of lymphocytes pre-and post-puberty and, that these changes during puberty may occur in response to sex hormones.Little is known about the mechanisms of immunomodulation by sexual hormones.Androgens can induce thymic involution by reducing the entry of bone marrow-derived stem cells in the thymus and by inducing the loss of thymic epithelial cells 26 .Lymphocytes are also influenced by androgens and, therefore, it is possible that the increase in connectivity observed after the age of 11 is the result of the interaction of memory T-cell subsets (CD4 + and CD8 + ) and B-cells with sex hormones.These processes occur as there are changes in the production, secretion and serum concentration of these endocrine components at this early period of lifetime.Along with sexual hormonal production, anthropometric data and previous infectious/parasitic diseases are aspects that could impact the immune response shaping the immune system over the years.However, in the present investigation, we do not have measure these variables.Thus, studies that better characterize the dynamics of changes in the profile of memory T and B-cells and other biological factors and their interactions can further contribute to a clear understanding of the early years of immunobiography.This is a pioneer investigation assessing the development of memory T and B-cell subsets during healthy childhood and adolescence in Minas Gerais, Brazil.However, the present study has some limitations.Despite the pioneering approach of this exploratory investigation, the observational design with multiple comparisons along ages during childhood development without corrections for the presence of parasitic/infectious diseases that may influence the profile of memory T and B-cells; nutritional aspects and hormonal measurements or other confounding variables constitute a limitation that may interfere in the interpretations of our findings.In the present study, we did not collect the hematological records to obtain the total lymphocyte counts for the study population and, therefore, the data were reported exclusively as relative percentages of cells within gated lymphocyte subsets and not as absolute cell numbers.Another limitation is that this is a single-center study in Belo Horizonte-Minas Gerais state, Brazil and the generalization of our findings to other epidemiological scenarios should be considered with caution.
Altogether, our findings demonstrated that the cell rhythmic signatures described here revealed a complex interaction between these cell subsets.Furthermore, the data highlighted the important changes that occurred during childhood development with rhythmic changes appearing at around 2 Yrs , with predominance of naive cells.Additionally, the second and more prominent wave occurred around the age 8-10 Yrs , with the prevalence of memory phenotypes.The neighborhood connectivity profile analysis also indicated a peak of integrative network Comprehensive networks were built for memory T-cell subsets (CD4 + and CD8 + ) and B-cells from healthy children and adolescents, categorized according to sex (Males (Blue color bar), n = 408 and Females (Red color bar), n = 404) followed by age stratification into distinct groups (9 Mths -1 Yr , n = 62, n = 73; 2 Yrs , n = 67, n = 80; 3-4 Yrs , n = 67, n = 62; 5-7 Yrs , n = 72, n = 61; 8-10 Yrs , n = 71, n = 69 and 11-18 Yrs , n = 69, n = 59, respectively).Data analyses were carried out by Spearman rank tests as described in Material and Methods.Networks were built using cluster layouts comprising four groups of memory cell phenotypes, including: NAIVE (N), Early EFFECTOR (eEF), CENTRAL/NON-CLASSICAL (CM/nCM) and EFFECTOR/CLASSICAL MEMORY (EM/ CM) subsets.Connecting edges identify positive (continuous line) and negative (dashed line) correlations.The line thickness illustrates the correlation strength, comprising weak/moderate ("r" scores from |0.1 to 0.67|, thin lines) and strong correlations ("r" scores from ≥|0.67|, thick lines).Common correlations axes are identified by blue/red lines and selective correlation axis observed at each age range are underscored by orange lines.The node sizes are proportional to the number of strong correlations between cell subsets.Memory cell phenotypes participating in at least 1 strong correlation are underscored by dark green nodes.The number of total and selective correlations between cell subsets at each age range as well as the number of common correlation axes along all age groups are provided in the figure.Circular backgrounds underscore the proportional contribution of each cell cluster to the overall connectivity at distinct age groups.www.nature.com/scientificreports/(Version 3.9.0.).Comprehensive heatmap constructs were assembled using the equalized distribution of subjects with results above the global median cut-offs employing the heatmap function of the Seaborn data visualization library (Version 0.11.2) of Python software (Version 3.9.0.).Correlation analysis was carried out using the Spearman rank test and the "r" scores of significant correlations (p < 0.05) employed to generate integrative networks using the systems biology approaches with the Cytoscape open-source platform (available at https:// cytos cape.org).The category cluster layout was chosen for arranging the networks of memory T and B-cell subsets.The memory cell phenotypes participating of at least one strong correlation ("r" scores from ≥|0.67|) were highlighted by darker nodes and the connecting edges underscored by thick dark lines.The number of connections between cell subsets was calculated and used for comparative analysis between age ranges.
Memory T and B-cells Along Childhood and Adolescence According to Sex Age Ranges

Figure 2 .
Figure 2. Rhythmic profile of memory T and B-cells along childhood and adolescence according to sex.The overall profile of memory T-cell subsets (CD4 + and CD8 + ) and B-cells was characterized in peripheral blood samples from healthy children and adolescents, categorized according to sex (Males (Blue color bar), n = 408 and Females (Red color bar), n = 404) followed by age stratification into distinct groups (9 Mths -1 Yr , n = 62, n = 73; 2 Yrs , n = 67, n = 80; 3-4 Yrs , n = 67, n = 62; 5-7 Yrs , n = 72, n = 61; 8-10 Yrs , n = 71, n = 69 and 11-18 Yrs , n = 69, n = 59, respectively).Immunophenotypic analysis of NAIVE (N), Early EFFECTOR (eEF), CENTRAL (CM) and EFFECTOR MEMORY (EM) T-cell subsets as well as NAIVE (N), Early EFFECTOR (eEF), NON-CLASSICAL MEMORY (nCM) and CLASSICAL MEMORY (CM) B-cells was carried out by flow cytometry as described in Material and Methods.The results are shown as scattering distribution of individual data of relative frequency of gated cells (% within CD4 + , CD8 + or CD19 + gated cells) over bars of median values for each age range.Comparative analysis between males and females at matching age ranges was carried out by Mann-Whitney test and significant differences at p < 0.05 underscored by #.Comparative analysis between pairs of adjacent age groups was carried out by Mann-Whitney test and significant differences at p < 0.05 underscored by connecting lines for comparisons with the immediately earlier age range and the statistical significance identified by *, **, ***, and **** for p values ≤ 0.05; ≤ 0.01, ≤ 0.001, and ≤ 0.0001, respectively.

Figure 3 .
Figure 3. Predicted probability of changes in memory T and B-cells along childhood and adolescence.The association between memory T-cell subsets (CD4 + and CD8 + ) and B-cells with childhood and adolescence was carried for healthy children and adolescents (ALL (Green circle), n = 812), further categorized according to sex (Males (Blue circle), n = 408 and Females (Red circle), n = 404).Data categorization was performed based on cutoffs established at the 75th percentile of each data set empirical distribution.The strength of association between the frequency of memory T-cell subsets and B-cells and age as well as putative variations by sex was assessed by logistic regression model as described in Material and Methods.Predicted probabilities were estimated by age and the final data shown as scattering distribution of changes in memory T-cell subsets and B-cells along age continuum (months) and significant differences considered at p < 0.05.The p values for the general population (ALL) and data stratification by sex (Males and Females) are provided in the figure.Significant p values are underscored in bold.
Panoramic Signatures of Memory T and B-cells Along Childhood and AdolescencePropor on of Subjects Above the Global Median Cut-off (%)

Figure 4 .
Figure 4. Panoramic signatures of memory T and B-cells along childhood and adolescence.(A) The overall signature of memory T-cell subsets (CD4 + and CD8 + ) and B-cells was assembled for healthy children and adolescents (ALL (Green color bar), n = 812), categorized according to distinct age groups (9 Mths -1 Yr , n = 135; 2 Yrs , n = 147; 3-4 Yrs , n = 129; 5-7 Yrs , n = 133; 8-10 Yrs , n = 140 and 11-18 Yrs , n = 128).Immunophenotypic analysis of NAIVE (N), Early EFFECTOR (eEF), CENTRAL (CM) and EFFECTOR MEMORY (EM) T-cell subsets as well as NAIVE (N), Early EFFECTOR (eEF), NON-CLASSICAL MEMORY (nCM) and CLASSICAL MEMORY (CM) B-cells was carried out by flow cytometry as described in Material and Methods.Signatures were assembled by first converting the original data, expressed as continuous variables (% of gated cells), into categorical results reported as proportion (%) of subjects with results above the cut-off edges (global median values of each cell subset).The final data are shown in radar chart, with each axis representing one memory cell subset.Cell phenotypes with proportion higher than the 50th percentile (gray zone) were underscored by *. (B) Heatmaps constructs were built to further illustrate the rhythmic distribution patterns of memory T-cell subsets and B-cells.Data are expressed as equalized distribution of subjects with results above the global median cut-off based on the color key provided in the figure.A white line set on the 50 th percentile of data distribution was used to define the overall rhythm of signatures of memory T-cell subsets and B-cells.
Heatmap of Memory T and B-cells Along Childhood and Adolescence According to Sex Subjects Above the Global Median Cut-off (%)

Figure 5 .
Figure 5. Signatures of memory T and B-cells along childhood and adolescence according to sex.(A) The overall signature of memory T-cell subsets (CD4 + and CD8 + ) and B-cells was assembled for healthy children and adolescents, categorized according to sex (Males (Blue color bar), n = 408 and Females (Red color bar), n = 404) followed by age stratification into distinct groups (9 Mths -1 Yr , n = 62, n = 73; 2 Yrs , n = 67, n = 80; 3-4 Yrs , n = 67, n = 62; 5-7 Yrs , n = 72, n = 61; 8-10 Yrs , n = 71, n = 69 and 11-18 Yrs , n = 69, n = 59, respectively).Immunophenotypic analysis of NAIVE (N), Early EFFECTOR (eEF), CENTRAL (CM) and EFFECTOR MEMORY (EM) T-cell subsets as well as NAIVE (N), Early EFFECTOR (eEF), NON-CLASSICAL MEMORY (nCM) and CLASSICAL MEMORY (CM) B-cells was carried out by flow cytometry as described in Material and Methods.Signatures were assembled by first converting the original data, expressed as continuous variables (% of gated cells), into categorical results reported as proportion (%) of subjects with results above the cut-off edges (global median values of each cell subset).The final data are shown in orbital chart, with each circle representing one memory cell subset with size and color proportional to the frequency (%) of subjects with results above the cut-off edges.(B) Heatmaps constructs were built to further illustrate the rhythmic distribution patterns of memory T-cell subsets and B-cells.Data are expressed as equalized distribution of subjects with results above the global median cut-off based on the color key provided in the figure.A white line set on the 50th percentile of data distribution was used to define the overall rhythm of memory T-cell subsets and B-cells signatures.

Figure 6 .
Figure 6.Integrative networks of memory T and B-cells along childhood and adolescence.Comprehensive networks were built for memory T-cell subsets (CD4 + and CD8 + ) and B-cells from healthy children and adolescents (ALL (Green color bar), n = 812), categorized into distinct age groups (9 Mths -1 Yr , n = 135; 2 Yrs , n = 147; 3-4 Yrs , n = 129; 5-7 Yrs , n = 133; 8-10 Yrs , n = 140 and 11-18 Yrs , n = 128).Data analyses were carried out by Spearman rank tests as described in Material and Methods.Networks were built using cluster layouts comprising four groups of memory cell phenotypes, including: NAIVE (N), Early EFFECTOR (eEF), CENTRAL/NON-CLASSICAL (CM/nCM) and EFFECTOR/CLASSICAL MEMORY (EM/CM) subsets.Connecting edges identify positive (continuous line) and negative (dashed line) correlations.The line thickness illustrates the correlation strength, comprising weak/moderate ("r" scores from |0.1 to 0.67|, thin lines) and strong correlations ("r" scores from ≥|0.67|, thick lines).Common correlations axis is identified by green lines and selective correlation axes observed at each age range are underscored by orange lines.The node sizes are proportional to the number of strong correlations between cell subsets.Cell subsets presenting at least 1 strong correlation are underscored by dark green nodes.The number of total and selective correlations axes between cell subsets at each age range as well as the number of common correlation axes along all age groups are provided in the figure.Circular backgrounds underscore the proportional contribution of each cell cluster to the overall connectivity at distinct age groups.

Figure 7 .
Figure 7. Integrative networks of memory T and B-cells along childhood and adolescence according to sex.Comprehensive networks were built for memory T-cell subsets (CD4 + and CD8 + ) and B-cells from healthy children and adolescents, categorized according to sex (Males (Blue color bar), n = 408 and Females (Red color bar), n = 404) followed by age stratification into distinct groups (9 Mths -1 Yr , n = 62, n = 73; 2 Yrs , n = 67, n = 80; 3-4 Yrs , n = 67, n = 62; 5-7 Yrs , n = 72, n = 61; 8-10 Yrs , n = 71, n = 69 and 11-18 Yrs , n = 69, n = 59, respectively).Data analyses were carried out by Spearman rank tests as described in Material and Methods.Networks were built using cluster layouts comprising four groups of memory cell phenotypes, including: NAIVE (N), Early EFFECTOR (eEF), CENTRAL/NON-CLASSICAL (CM/nCM) and EFFECTOR/CLASSICAL MEMORY (EM/ CM) subsets.Connecting edges identify positive (continuous line) and negative (dashed line) correlations.The line thickness illustrates the correlation strength, comprising weak/moderate ("r" scores from |0.1 to 0.67|, thin lines) and strong correlations ("r" scores from ≥|0.67|, thick lines).Common correlations axes are identified by blue/red lines and selective correlation axis observed at each age range are underscored by orange lines.The node sizes are proportional to the number of strong correlations between cell subsets.Memory cell phenotypes participating in at least 1 strong correlation are underscored by dark green nodes.The number of total and selective correlations between cell subsets at each age range as well as the number of common correlation axes along all age groups are provided in the figure.Circular backgrounds underscore the proportional contribution of each cell cluster to the overall connectivity at distinct age groups. https://doi.org/10.1038/s41598-023-48115-3