Molecular Pathways Mediating Immunosuppression in Response to Prolonged Intensive Physical Training, Low-Energy Availability, and Intensive Weight Loss

Abstract

Exercise and exercise-induced weight loss have a beneficial effect on overall health, including positive effects on molecular pathways associated with immune function, especially in overweight individuals. The main aim of our study was to assess how energy deprivation (i.e., "semi-starvation") leading to substantial fat mass loss affects the immune system and immunosuppression in previously normal weight individuals. Thus, to address this hypothesis, we applied a high-throughput systems biology approach to better characterize potential key pathways associated with immune system modulation during intensive weight loss and subsequent weight regain. We examined 42 healthy female physique athletes (age 27.5 ± 4.0 years, body mass index 23.4 ± 1.7 kg/m²) volunteered into either a diet group (n = 25) or a control group (n = 17). For the diet group, the energy intake was reduced and exercise levels were increased to induce loss of fat mass that was subsequently regained during a recovery period. The control group was instructed to maintain their typical lifestyle, exercise levels, and energy intake at a constant level. For quantification of systems biology markers, fasting blood samples were drawn at three time points: baseline (PRE), at the end of the weight loss period (MID 21.1 ± 3.1 weeks after PRE), and at the end of the weight regain period (POST 18.4 ± 2.9 weeks after MID). In contrast to the control group, the diet group showed significant (false discovery rate <0.05) alteration of all measured immune function parameters-white blood cells (WBCs), immunoglobulin G glycome, leukocyte transcriptome, and cytokine profile. Integrative omics suggested effects on multiple levels of immune system as dysregulated hematopoiesis, suppressed immune cell proliferation, attenuated systemic inflammation, and loss of immune cell function by reduced antibody and chemokine secretion was implied after intense weight loss. During the weight regain period, the majority of the measured immune system parameters returned back to the baseline. In summary, this study elucidated a number of molecular pathways presumably explaining immunosuppression in individuals going through prolonged periods of intense training with low-energy availability. Our findings also reinforce the perception that the way in which weight loss is achieved (i.e., dietary restriction, exercise, or both) has a distinct effect on how the immune system is modulated.

Keywords: bioinformatics; immunosuppression; low energy availability; physical training; weight loss.

Figure 1

Study design and workflow. Study design and workflow are represented in a flowchart to illustrate the whole study protocol used. ^*Of the 60 participants who started the study, 10 failed to complete the study regimen in a required manner. One control did not arrive for baseline testing (PRE) and the remaining nine participants (three from the diet group and six controls) were excluded out of the study because of a short duration of the weight regain period compared with the other participants or failure to completely follow the study instructions. Additional participants that lacked complete dietary records (n = 8) were excluded from the current omics study. Due to the high cost of large-scale data-set quantification, only individuals with minimal missing information were included in the study sample. After data quality control, also additional individuals were excluded from the analysis. The final number of participants used for the analysis on each data set is depicted in the figure. In total, we included samples from 42 participants (diet group n = 25, control group n = 17) in the bioinformatic analysis after the relevant exclusions. For the cytokine profile quantification, samples from only 30 individuals were analyzed due to high-cost of the analysis panel. Furthermore, sample size varied slightly between different downstream analyses due to incompleteness of omics or phenotype data.

Figure 2

Transcription regulators of hematopoiesis and blood cell count alteration following intense weight loss. Here, we demonstrate alterations occurring in hematopoiesis regulation and subsequent changes in circulating blood cells. In particular, suppressed differentiation in erythroid lineage and induced activity of leukocyte progenitor cell lines (myeloid, lymphoid) were suggested by increased SPI1 and reduced GATA transcription factor expression levels. Panel (A) depicts absolute levels of different categories of quantified blood cells, whereas panel (B) demonstrates downstream modulation of transcription factors affecting blood cell formation. Ctrl, control; NS, not significant (P > 0.05 on panel (A), false discovery rate, FDR > 0.05 on panel (B). Granulocytes depicted in the figure include basophils, eosinophils, and monocytes (i.e., mixed cells). Box-plot elements are defined as follows: center line, median; box limits, upper and lower quartiles; whiskers, 1.5× interquartile range.

Figure 3

Differentially expressed genes related to innate and adaptive immune system function after the prolonged period of low-energy availability. Heat map of differentially expressed genes depicts alteration in RNA expression levels that belong to immune function related pathways after the weight loss period when compared with controls (PRE–MID). Heat map is derived from DESeq2 normalized expression levels (read counts) that are represented as standard deviation (SD) change from the reference Z-score. The baseline calculated Z-score values (PRE) from both the diet and control groups were pooled together and set as the reference level to which each individual group/time-point level was compared. On the heat map, blue colors indicate decrease and red colors increase in gene expression level compared with the calculated reference value. FDR = false discovery rate. Adjusted P-values are represented in front of each HGNC gene symbol name. FDR > 0.2 was set as not significant (NS).

Figure 4

Immunoglobulin G (IgG) glycosylation peak modulation and expression changes in associated transcriptomic regulators after the intense weight loss period. Overall, this figure shows IgG glycosylation changes in the diet group during the study. Polar plots are derived from IgG glycosylation peak raw values where outliers based on four standard deviations (SDs) from the mean have been excluded. Plotted values are represented as SD change from the set reference Z-score. Red color indicates increase and blue a decrease compared with the reference Z-score. Height of the bars depicts the Z-score level, and the scale is plotted on the figure vertically. Significant time-dependent changes are assigned on the figure with an asterisk (^*). IgG glycosylation peaks are ordered based on panel (A) for the diet group. Z-score reference values for the diet group were determined from the baseline values. Panels (A,B) demonstrate diet group IgG glycosylation changes after the weight loss period (panel A, PRE–MID) and after the whole study period (panel B, PRE–POST). Panel (C) demonstrates expression levels observed in transcription factors associated with IgG glycosylation. P-values in panel (C) have been adjusted for multiple testing by using false discovery rate (FDR). Significance threshold was set to FDR < 0.05. Box-plot elements are defined as follows: center line, median; box limits, upper, and lower quartiles; whiskers, 1.5 × interquartile range.

Figure 5

Effect of low-energy availability on cytokine profile alteration in the study participants. Panel (A) line plots show that cytokines were altered significantly in a time-dependent manner during the weight loss period (PRE–MID) in the diet group. The red line represents the control group, whereas the blue line depicts the diet group. Error bars are depicted as standard error (SE). Significant time-dependent changes compared with baseline (PRE) are depicted with asterisks, where ^* = false discovery rate (FDR) < 0.05. Panel (B) depicts a heat map of the entire measured cytokine profile, including the ones with significant time-dependent changes shown in the panel (A). Cytokine levels are represented as standard deviation (SD) change from the reference Z-score. Baseline calculated Z-score values (PRE) from both the diet and control groups were pooled together and set as the reference level to which each individual group/time-point level was compared. On the heat map, blue colors indicate decrease and red colors increase in cytokine level compared with the calculated reference value. FDR adjusted P-values for within-group time-point comparisons are depicted in front of the cytokine names. Panel (B) demonstrates clearly that despite only a handful of significant time-dependent changes seen in panel (A) in the diet group, the overall cytokine levels are notably lower in the diet group when compared with the control group.