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Additional file 1: Table S1. Summary of antibody and cell-mediated immune responses pre- and 4-weeks post-influenza vaccination. Table S2. Results from multivariable analysis of vaccine antibody responses in older adults where plasma TNF, IL-6 and CRP were simultaneously included as fixed effects. Table S3. Summary of participants enrolled in the follow-up cohort, including pre-vaccination levels of inflammatory mediators and antibody responses pre- and 4-weeks post-influenza vaccination. Figure S1. Associations between inflammatory mediator levels and antibody responses of high-dose vaccine recipients are independent of frailty. Figure S2. Joint effects of TNF and IL-6 in the association with post-vaccination antibody titres in standard- dose (SD) and high-dose (HD) older recipients. Figure S3. Sex-stratified models of systemic inflammation and the response to influenza vaccination in young (YA) and older (OA) adults vaccinated with either standard (SD) or high (HD) dose vaccine. Figure S4. ILT2+CD57+ Dim NK-cells mediate a significant proportion of the effect of frailty on post-vaccination A/H3N2 antibody titres in older high-dose recipients.

Additional file 1: Supplementary Table 1. Regression table describing the association between standardized, natural-log 4-week antibody titres and ΔBA in high-dose recipients, including a two-way interaction between ΔBA and CMV serostatus. Supplementary Table 2. KDM training parameters derived from the CLSA and used calculate biological aging in the vaccination cohort. Supplementary Figure 1. Characteristics of KDM biological age (BA) in the CLSA training cohort and associations with the frailty index (FI). A) Pearson’s correlation (R) for BA with chronological age and significance (p) for females (red asterisk) and males (blue dots). B) Distribution of ΔBA in females and males, including the mean and standard deviation. C) Differences in years for ΔBA (and 95% confidence interval) for pre-frail (0.10=FI

Additional file 1: Supplementary Table 1–8. The association of adaptive immune cell phenotypes with metabolically healthy obesity.

Additional file 1: Figure S1. (A) CC is greatest in lattice networks (blue) and lowest in random networks (green), whereas CC for the real networks (red) is in-between. In contrast, (B) CPL is shortest in random and longest in lattice networks, while the real networks are in-between. CMV, Cytomegalovirus; CMV- m, CMV-seronegative men; CMV+ m, CMV-seropositive men; CMV- f, CMV-seronegative women; CMV+ f, CMV-seropositive women. Figure S2. (A) Local efficiency was highest in regular networks (at least for the cost levels under 45%) and lowest in random networks (at least for the cost levels under 20%), while (B) global efficiency was highest in random (green) and lowest in lattice (blue) networks practically for all levels of wiring costs, with real (red) networks were always in-between. CMV, Cytomegalovirus; CMV- m, CMV-seronegative men; CMV+ m, CMV-seropositive men; CMV- f, CMV-seronegative women; CMV+ f, CMV-seropositive women.

DFS and OS in patients according to standard clinicopathological variables. Figures S2-S5. DFS (A, C) and OS (B, D) for patients stratified by grade (Figure S2), T status (Figure S3), nodal status (Figure S4) and pathological TNM stage (Figure S5) and analyzed according to the density of CD8+ (A, B) or CD163+ (C, D) cells in TC or IM. Figures S6-S9. Kaplan-Meier curves illustrating DFS (A, C, E) and OS (B, D, E) for patients stratified by grade (Figure S6), T status (Figure S7), nodal status (Figure S8) and pathological TNM stage (Figure S9) and analyzed according to the density of CD8+ (A, B) or CD163+ (C, D) cells in the combined tumor regions and to the combined immune signatures (E, F). The statistics with significant differences or strong trends between groups and the corresponding hazard ratios are shown in the respective plots. (PDF 356Â kb)

Leukocyte phenotypes examined in peripheral blood (PPTX 78 kb)

Clinical characteristics of the control and chemotherapy patient groups (DOCX 23 kb)

Gating strategy used to identify regulatory T cells (PPTX 182 kb)

Estimated mean blood leukocyte levels (with 95% confidence intervals) in patients undergoing chemotherapy (green lines) or without chemotherapy (blue lines) at baseline and at 3Â months and 12Â months after starting therapy (PPTX 1131 kb)

Gating strategy used to identify myeloid cells including myeloid-derived suppressor cells (PPTX 189 kb)

Gating strategy used to identify T cell subsets and differentiation stages (PPTX 227 kb)

Results of Mann‐Whitney comparisons of the γδ T‐cell compartments and subsets. Table S2. Results of Mann‐Whitney comparisons of the CD8+ γδ T‐cell compartments and subsets. Table S3. Results of Mann‐Whitney comparisons of the αβT‐cell compartments and subsets. Table S4. Results of Mann‐Whitney comparisons of the absolute counts for all T‐cell compartments. Figure S1. Median frequencies and absolute counts of the γδ T‐cell compartments in young and old CMV‐seropositive (CMV+) and seronegative (CMV‐) individuals. Figure S2. Differentiation phenotypes of the Vδ2+ compartment. Figure S3. Differentiation phenotypes of the Vδ1+ compartment. Figure S4. Differentiation phenotypes of the Vδ1‐Vδ2‐compartment. Figure S5. Differentiation phenotypes of the CD8+ γδ T‐cells. Figure S6. Differentiation phenotypes of the CD8+ αβT‐cells. Figure S7. Differentiation phenotypes of the CD4 + αβT‐cells. Figure S8. Gating Strategy T‐cells. (PDF 1365 kb)

CD8+ and CD4+ T-cell response to Her-2: A representative plot of control and Her-2-stimulated cytokine (eg.TNF-producing CD8+ T-cells and CD4+ T-cells). (PPTX 89Â kb)

Clinico-pathological characteristics of younger and older patients. (DOCX 15Â kb)

Additional file 2: Table S1. Patients clinico-pathological parameters.

Additional file 1. Representative FACS plots and additional results.

Background Aging and latent infection with Cytomegalovirus (CMV) are thought to be major factors driving the immune system towards immunosenescence, primarily characterized by reduced amounts of naïve T-cells and increased memory T-cells, potentially associated with higher morbidity and mortality. The composition of both major compartments, γδ as well as αβ T-cells, is altered by age and CMV, but detailed knowledge of changes to the γδ subset is currently limited. Results Here, we have surveyed a population of 73 younger (23–35 years) and 144 older (62–85 years) individuals drawn from the Berlin Aging Study II, investigating the distribution of detailed differentiation phenotypes of both γδ and αβ T-cells. Correlation of frequencies and absolute counts of the identified phenotypes with age and the presence of CMV revealed a lower abundance of Vδ2-positive and a higher amount of Vδ1-positive cells. We found higher frequencies of late-differentiated and lower frequencies of early-differentiated cells in the Vδ1+ and Vδ1-Vδ2-, but not in the Vδ2+ populations in elderly CMV-seropositive individuals confirming the association of these Vδ2-negative cells with CMV-immunosurveillance. We identified the highest Vδ1:Vδ2 ratios in the CMV-seropositive elderly. The observed increased CD4:CD8 ratios in the elderly were significantly lower in CMV-seropositive individuals, who also possessed a lower naïve and a larger late-differentiated compartment of CD8+ αβ T-cells, reflecting the consensus in the literature. Conclusions Our findings illustrate in detail the strong influence of CMV on the abundance and differentiation pattern of γδ T-cells as well as αβ T-cells in older and younger people. Mechanisms responsible for the phenotypic alterations in the γδ T-cell compartment, associated both with the presence of CMV and with age require further clarification.

CD8+ and CD4+ T-cell response to Her-2: A representative plot of control and Her-2-stimulated cytokine (eg.TNF-producing CD8+ T-cells and CD4+ T-cells). (PPTX 89Â kb)

Kaplan-Meier analysis of clinico-pathological parameters in older patients. (DOCX 17Â kb)

Additional file 2: Table S1. Patients clinico-pathological parameters.

Additional file 1. Representative FACS plots and additional results.

Kaplan-Meier analysis of clinico-pathological parameters in older patients. (DOCX 17Â kb)

Clinico-pathological characteristics of younger and older patients. (DOCX 15Â kb)