Characteristics of the sample
We analyzed 437 of 1671 older participants (60-84 years) of the BASE-II study, medically assessed at baseline, based on the availability of immunological parameters. The sample analyzed in this study was composed of participants with an equal gender distribution. Table 1 shows the median age, BMI, metabolic measurements (HbA1c, insulin sensitivity index (ISIOGTT), homeostasis model of assessment for insulin resistance (HOMA-IR)), glucose and insulin parameters measured in oral glucose tolerance tests (OGTT) and lipid parameters), hematologic parameters, and plasma C-reactive protein (CRP) levels of male and female participants. All hematologic parameters and CRP levels were within the normal range (NR). Obesity was noted in 28 of 181 men (15.5%) and 49 of 256 women (19.1%) (defined as BMI > 30 kg/m2), whereas 6.6% (women) and 11% (men) were diagnosed with type 2 diabetes. Participants with type 2 diabetes were ruled out for further analyses. However, 31.8% of the men and 28.8% of the women were considered IR at least to some extent, with insulin resistance being defined as ISIOGTT < 4. Surprisingly, only 50% of all obese participants analyzed in this study had an ISIOGTT < 4, and only 32% of all obese participants were considered truly IR, as assessed by HOMA-IR (HOMA-IR > 2.9).
Impaired insulin sensitivity is associated with increased T cell senescence
As expected, the BMI was negatively associated with ISIOGTT in both male and female participants (Figure 1A). The ISIOGTT also correlated negatively with the total number of leukocytes, obtained from complete blood count results (Figure 1B), in line with previous results from another study of ours (18). To assess the association of metabolic parameters (BMI, HOMA-IR, ISIOGTT) with systemic leukocyte subpopulations, we analyzed multiparameter flow cytometric data derived from blood samples of older participants. To analyze gender-specific differences, we here calculated each correlation independently for men and women. Whereas the percentages of major mononuclear leukocyte subsets (CD4+ and CD8+ T cells, CD19+ B cells, CD56+NK cells, and CD14+monocytes) did not significantly correlate with BMI, HOMA-IR or ISIOGTT, we found that the percentages of naïve (CD45RA+CCR7+CD27+CD28+) CD4+ and CD8+ T cell subsets (the latter only within the female subgroup) were positively associated with ISIOGTT and negatively associated with HOMA-IR in older participants, whereas the percentage of central memory (CD45RA-CD27+CD28+) CD4+ T cells was negatively associated with ISIOGTT and positively associated with HOMA-IR (Figure 1C-E, Supplementary Table 1). However, neither men nor women exhibited a significant correlation between the percentage of central memory CD8+ T cells and the ISIOGTT (Figure 1F). The percentage of effector memory (CD45RA-CD27-CD28-) CD8+ T cells correlated positively with HOMA-IR, but other T cell subsets (exhausted PD1+ T cells or terminally differentiated effector memory T cells) did not show significant associations with metabolic measures (Supplementary Table 1). While regulatory T (Treg) cells have been reported to play a role in regulating obesity-induced adipose tissue inflammation (19), the percentage of circulating FoxP3+CD25high Treg cells within the CD4+ T cell subset was not associated with BMI, HOMA-IR or ISIOGTT in this study (Figure 1G, Supplementary Table 1). However, CD8+ FoxP3+ Treg cells, which have been reported recently to be critical in prevention of autoimmune-mediated diabetes, correlated positively with BMI (data not shown). The different subsets of B cells did not correlate significantly with metabolic measures. Whereas the percentage of CD14-CD16+ monocytes correlated inversely with HOMA-IR and ISIOGTT, other monocyte subsets did not exhibit significant correlations (Supplementary Table 1). Additionally, we correlated cytokine levels (IL-6, IL-10, TNF, IL-1ß) with metabolic measures. As described previously (20), the seminal inflammatory marker IL-6 was negatively associated with ISIOGTT in female participants (Figure 1H), but the associations between IL-10, TNF, IL-1ß and metabolic measures were not significant (data not shown). CD57 has been proposed as a marker for T cell senescence, as its expression is associated with impaired proliferative capacity and other characteristics of senescence (21). However, CD57 can also define activated immunoregulatory-like cells (22). Here, we found a positive association of CD57 expression on central memory CD8+ T cells with BMI, whereas CD57+ effector memory CD8+ T cells correlated positively with HOMA-IR (Supplementary Table 1). With age, the distribution of circulating T cells at different stages of differentiation changes drastically, as a result of the minimal production of naïve T cells, and the accumulation of senescent-like CD28-CD57+CD8+T cells, which have been shown to be associated with reduced immune response to pathogens in the elderly (22). This could contribute to increased severity of infections in the older population (23). Taken together, our findings thus imply that insulin resistance is associated with a higher “age” of circulating T cells. Since the serostatus of CMV can affect the phenotype of immune cell subsets as well (24), we additionally correlated the BMI and ISIOGTT with immune cell parameters from CMV seronegative and seropositive participants. We found that the correlation coefficients were influenced by the CMV serostatus and that some significant correlations between T cell subsets, BMI and ISIOGTT were found in CMV+, but not CMV- participants.
T cells have a more activated phenotype in IS versus IR obese individuals
To better characterize the immunological differences between IS, who are considered metabolically healthy, and IR (considered metabolically unhealthy) obese and non-obese participants of this study, we stratified the cohort into four groups by the ISIOGTT. The BMI was significantly lower in non-obese IS participants (Figure 2A) but did not differ significantly between IS and IR obese participants. As expected, ISIOGTT, HOMA-IR and HbA1c were significantly different between IS and IR obese and non-obese participants (Figure 2B, C and E), whereas CRP, triglyceride and LDL cholesterol levels, and age did not differ significantly between groups (Figure 2D and F-H). The frequencies of naïve CD8+ T cells were significantly higher in obese and non-obese IS compared to IR participants, whereas the frequencies of effector memory and CD57+ antigen-experienced and differentiated CD8+ T cells were significantly lower in obese IS compared to IR individuals (Figure 2I-K). Additionally, IL-6 levels, which have previously been reported to promote insulin resistance (20), were higher in obese IR than IS individuals (Figure 2L). In the CD4+ T cell compartment, frequencies of naïve CD4+ T cells were higher and frequencies of central memory CD4+ T cells were lower in IS versus IR non-obese individuals, while we did not see any significant differences in the obese group (Figure 2M-O, Supplementary Table 3). No significant differences between groups were found for other T cell subsets, B cells, NK cells, monocytes or CD4+ Treg cells (Supplementary Table 3). In addition, the levels of the anti-inflammatory cytokine IL-10 (Figure 2P), TNF and IL-1ß were not significantly different in the obese and non-obese subgroups (Supplementary Table 4). TNF and IL-1ß were undetectable in some participants, and these were excluded in further studies. These findings suggest that senescence of circulating T cells reflects a major difference between IS and IR participants in both obese and non-obese subgroups.
The percentage of naïve CD4+ and CD8+ T cells predicts impaired insulin sensitivity
Next, we tested the association of ISIOGTT with systemic leukocyte subsets and cytokine levels in multivariable linear regression models. The frequencies of T cells, Treg cells, monocytes, B cells, and NK cells were not significantly associated with ISIOGTT, neither after adjustment for sex and BMI (model 1) nor with additional adjustment for the morbidity index and cytomegalovirus (CMV) status (model 2). More details of these results that are in line with our findings that the proportions of major innate and adaptive leukocyte subsets (T cells, Treg cells, monocytes, B cells, and NK cells) were not significantly different in obese or non-obese IR and IS participants can be found in Supplementary Table 5. T stem cell-like memory T cells (TSCM, defined as CD45RA+CCR7+CD27+CD28+CD95+) were also not significantly associated with ISIOGTT (Supplementary Table 5). Table 2 summarizes the regression analyses of naïve, central, effector, and terminally differentiated effector memory CD4+ and CD8+ T cells on ISIOGTT. Whereas central and terminally differentiated effector memory CD4+ and CD8+ T cells did not predict ISIOGTT, naïve CD4+ and CD8+ T cells, and central memory CD4+ T cells were significantly associated with ISIOGTT. Of note, this significant association was independent of sex, BMI, and even after adjustment for the morbidity index and CMV status in model 2, the associations of naïve CD4+ T cells and ISIOGTT remained significant (Table 2, Supplementary Table 5). We replicated these findings using an additional binary logistic regression model (Supplementary Table 6). To account for potential selectivity based on high age, we also added a sensitivity analysis, and ruled out participants, that were aged 80 years or older (8 participants, age 80-84 years). None of those participants were obese and the results remained unchanged (Supplementary Table 7). CMV was included in this analysis because latent infection with this herpesvirus strongly influences circulating naïve and memory T cell phenotypes (25). Circulating IL-6 and IL-10 levels were not significantly associated with ISIOGTT (data not shown). Taken together, these data indicate that the differentiation and activation state of CD4+ and CD8+ T cells is strongly associated with insulin resistance.