2.1. Study 1: Effect of Supplementation with Vitamin D on PBMC Fatty Acid Levels
PBMC samples from subjects (N = 8) receiving a vitamin D supplement or a placebo were isolated and the FA profiled. The subjects in the supplemented and placebo groups did not significantly differ by age, BMI (
Table 1), as well as dietary intakes of SFA, MUFA and PUFA.
In Study 1, several biochemical markers related to metabolic health and inflammation were measured. Circulating 25(OH)D levels increased significantly in the supplemented compared to the placebo group (56.2 ± 18.9 nmol/L
vs. 30.4 ± 8.6 vs.
p = 0.029) (
Table 3). There were no significant differences in the metabolic health and inflammatory parameters measured
Table 1.
Participants’ characteristics in Study 1.
| Placebo, N = 4 | | Vitamin D, N = 4 | | p |
---|
| Mean | SD | Mean | SD | |
Age (y) | 53.8 | 7.3 | 52.5 | 7.5 | 0.802 |
Height (m) | 1.77 | 0.11 | 1.69 | 0.11 | 0.344 |
Weight (kg) | 84.8 | 13.6 | 70.5 | 16.3 | 0.211 |
BMI (kg/m2) | 27.0 | 3.2 | 24.3 | 2.8 | 0.215 |
Table 2.
Participants’ characteristics in Study 2
| Female, N = 10 | | Male, N = 10 | | p |
---|
| Mean | SD | Mean | SD | |
Age (y) | 27.2 | 4.5 | 30.6 | 5.0 | 0.126 |
Height (m) | 1.68 | 0.05 | 1.81 | 0.07 | 0.002 |
Weight (kg) | 55.2 | 5.24 | 79.9 | 11.3 | 3 × 10-5 |
BMI (kg/m2) | 19.5 | 1.5 | 24.3 | 3.1 | 0.001 |
Table 3.
Biochemical markers of subjects in the vitamin D3 supplemented and placebo groups (Study 1). NEFA, non-esterified fatty acids; TG, triglycerides.
| Placebo | | Vitamin D | | p * |
---|
| Mean | SD | Mean | SD | |
25(OH)D (mmol/L) | 30.4 | 8.6 | 56.2 | 18.9 | 0.029 |
hsCRP (mg/L) | 2.8 | 3.6 | 1.0 | 0.4 | 0.368 |
IL-6 (pg/mL) | 2.2 | 3.3 | 0.6 | 0.1 | 0.362 |
TNFalpha (pg/mL) | 4.0 | 1.0 | 3.6 | 1.1 | 0.541 |
Glucose (mmol/L) | 5.7 | 0.4 | 5.6 | 0.1 | 0.555 |
Insulin (µU/mL) | 3.2 | 1.8 | 3.5 | 2.8 | 0.837 |
TG(mmol/L) | 1.0 | 0.2 | 1.4 | 0.5 | 0.164 |
NEFA (mmol/L) | 0.4 | 0.2 | 0.6 | 0.2 | 0.247 |
Total cholesterol (mmol/L) | 6.4 | 0.7 | 5.7 | 0.5 | 0.105 |
HDL (mmol/L) | 1.3 | 0.4 | 1.4 | 0.4 | 0.749 |
LDL (mmol/L) | 4.5 | 0.3 | 3.9 | 0.3 | 0.030 |
Adiponectin (µg/mL) | 6.0 | 4.1 | 5.7 | 2.2 | 0.896 |
Leptin (ng/mL) | 0.9 | 0.5 | 0.7 | 0.5 | 0.617 |
Resistin (ng/mL) | 3.9 | 0.6 | 3.0 | 1.1 | 0.178 |
Ferritin (ng/mL) | 65.6 | 39.1 | 72.0 | 27.0 | 0.791 |
The most abundant FA in the cells were as follows (given in descending order): C20:4n6, C18:0, C16:0 and C18:1n9c and comprised around 85% of the total FA present in the PBMC cell. There was no significant difference in the FA in the supplemented group compared to the placebo group (
Table 4).
Table 4.
Fatty acids PBMC profile in vitamin D and placebo groups (Study 1).
Fatty Acid (%) | Placebo | | Vitamin D | | p * | q |
---|
| Mean | SD | Mean | SD | | |
C16:0 (palmitic acid) | 18.3 | 2.2 | 19.5 | 1.0 | 0.373 | 0.667 |
C18:0 (stearic acid) | 23.6 | 2.2 | 22.1 | 0.5 | 0.258 | 0.667 |
C18:1n9c (oleic acid-cis) | 13.1 | 1.3 | 13.2 | 1.2 | 0.880 | 0.667 |
C18:1n9t (elaidic acid) | 1.6 | 0.3 | 1.5 | 0.2 | 0.918 | 0.693 |
C18:2n6 (linoleic acid) | 7.7 | 1.5 | 7.3 | 0.8 | 0.604 | 0.693 |
C20:4n6 (arachidonic acid) | 30.6 | 3.0 | 30.7 | 2.4 | 0.949 | 0.693 |
C20:3n6 (osatrienoic acid) | 1.7 | 0.1 | 2.0 | 0.3 | 0.149 | 0.667 |
C20:0 (arachidic acid) | 1.1 | 0.1 | 1.0 | 0.1 | 0.254 | 0.684 |
C22:0 (behenic acid) | 1.0 | 0.3 | 1.1 | 0.1 | 0.313 | 0.684 |
C24:1 (nervonic acid) | 0.9 | 0.1 | 1.0 | 0.3 | 0.220 | 0.667 |
C24:0 (lignoceric acid) | 0.5 | 0.0 | 0.5 | 0.1 | 0.740 | 0.725 |
SFA | 44.5 | 3.9 | 44.3 | 1.3 | 0.933 | 0.745 |
MUFA | 15.5 | 1.2 | 15.7 | 1.6 | 0.773 | 0.667 |
PUFA | 40.0 | 3.9 | 39.9 | 2.0 | 0.963 | 0.693 |
2.3. Examination of Fatty Acids and Amino Acids Levels in PBMCs (Study 2)
In the second study, 20 subjects were recruited in order to assess if the PBMC metabolic profile differs between genders. No difference in age between male and female participants was observed in the second study. However, females had significantly lower BMI (19.5 ± 1.5 kg/m
2) compared to males (24.3 ± 3.1 kg/m
2) (
p = 0.001) (
Table 2).
A total of 11 FA present in PBMC were identified and quantified (
Table 5). After controlling for BMI, there was a significant difference observed for C16:0 (
p = 0.025), C18:1n9c (
p = 0.018) and total MUFA (
p = 0.015) between males and females. However, using a false discovery rate(FDR )at 5% revealed that none of these were significantly different between the genders. In addition, 10 amino acids (AA) were profiled and quantified (
Table 6). In the unadjusted model, the percentage of isoleucine (
p = 0.003) was significantly higher in males
vs. females. Aspartic acid was lower in the PBMC from males (
p = 0.02). After adjustment for BMI, no significant differences were observed between the groups, suggesting a confounding effect of BMI.
In subsequent analysis by BMI groups (low vs. high), valine (2.1 ± 0.5 vs. 3.1 ± 0.7%, p = 0.02) and isoleucine (2.1 ± 0.4 vs. 2.7 ± 0.4%, p = 0.011) were lower, and aspartic acid (11.3 ± 2.3 vs. 8.0 ± 2.0% p = 0.003) was significantly higher in the lower BMI group (BMI ≤ 20.6 kg/m2). There was no significant difference in the FA levels between the BMI groups.
Table 5.
Fatty acids profile of PBMC in female and male subjects (Study 2).
w/w (%) | Female | | Male | | p * | p ** | q |
---|
| Mean | SD | Mean | SD | | | |
C16:0 (palmitic acid) | 23.9 | 2.4 | 19.6 | 4.0 | 0.008 | 0.039 | 0.096 |
C18:0 (stearic acid) | 26.9 | 4.5 | 23.3 | 7.0 | 0.189 | 0.373 | 0.268 |
C18:1n9c (oleic acid-cis) | 12.7 | 1.0 | 12.7 | 2.0 | 0.998 | 0.020 | 0.849 |
C18:1n9t (elaidic acid) | 2.7 | 1.2 | 2.0 | 1.6 | 0.314 | 0.351 | 0.363 |
C18:2n6 (linoleic acid) | 3.6 | 1.2 | 4.2 | 1.0 | 0.291 | 0.358 | 0.363 |
C20:4n6 (arachidonic acid) | 25.5 | 6.3 | 33.0 | 10.7 | 0.072 | 0.090 | 0.191 |
C20:3n6 (osatrienoic acid) | 1.6 | 0.8 | 1.3 | 0.4 | 0.379 | 0.721 | 0.399 |
C20:0 (arachidic acid) | 0.5 | 0.1 | 0.6 | 0.1 | 0.061 | 0.172 | 0.191 |
C22:0 (behenic acid) | 1.2 | 0.2 | 1.7 | 0.6 | 0.015 | 0.274 | 0.096 |
C24:1 (nervonic acid) | 0.7 | 0.2 | 0.7 | 0.2 | 0.932 | 0.669 | 0.849 |
C24:0 (lignoceric acid) | 0.7 | 0.3 | 0.8 | 0.3 | 0.161 | 0.771 | 0.268 |
SFA | 53.2 | 6.3 | 46.1 | 10.1 | 0.075 | 0.172 | 0.191 |
MUFA | 16.1 | 1.7 | 15.4 | 2.3 | 0.486 | 0.020 | 0.477 |
PUFA | 30.7 | 7.8 | 38.5 | 11.3 | 0.090 | 0.106 | 0.191 |
Table 6.
Amino acids profile of PBMC in female and male subjects (Study 2).
w/w (%) | Female | | Male | | p * | p ** | q |
---|
| Mean | SD | Mean | SD | | | |
Alanine | 8.8 | 1.4 | 9.4 | 1.7 | 0.366 | 0.449 | 0.732 |
Valine | 2.3 | 0.5 | 2.9 | 0.8 | 0.034 | 0.694 | 0.117 |
Leucine | 1.6 | 0.6 | 1.9 | 0.6 | 0.247 | 0.596 | 0.62 |
Isoleucine | 2.1 | 0.4 | 2.7 | 0.4 | 0.004 | 0.175 | 0.04 |
Glycine | 6.1 | 1.9 | 6.6 | 1.2 | 0.477 | 0.634 | 0.792 |
Serine | 3.5 | 0.5 | 3.5 | 0.8 | 0.995 | 0.929 | 0.994 |
Threonine | 1.2 | 0.3 | 1.2 | 0.3 | 0.939 | 0.678 | 0.994 |
Proline | 50.2 | 4.0 | 49.9 | 4.3 | 0.872 | 0.866 | 0.994 |
Aspartic acid | 11.0 | 2.6 | 8.2 | 2.1 | 0.017 | 0.578 | 0.085 |
Glutamine | 13.3 | 2.5 | 13.6 | 1.4 | 0.723 | 0.621 | 0.994 |
2.4. Discussion
Transcriptomic analysis of PBMCs has been successfully implemented in nutrition research [
17]. To date, there has been relatively few examples of metabolomic applications using PBMCs. However, this potential application holds great promise and may in fact yield more useful biological information with respect to inflammatory processes compared to analysis of serum or plasma. Moreover, the important interplay between metabolism and immunology has recently come to light [
18]. Application of the approach developed here could greatly enhance the interpretation of metabolic responses in immune cells. In the present study, there were no differences in the FA profile of PBMCs in the vitamin D supplemented group compared to a placebo group. However, several of the FAs were significantly correlated with biochemical markers. In the second part of the study, the metabolic profile of the PBMC was expanded to AA, and comparison across genders revealed BMI-, but not gender-, specific AA.
Proportions of FA identified in the PBMC were comparable to the results obtained in other studies [
10,
19] and closely reproduced the proportions of FA found in the liver in another study [
20]. As expected, the most abundant was arachidonic acid (20:4n6), a main energy source for activated immunologic cells that plays an important role in the control of cellular metabolism during inflammation [
21,
22].
Since the discovery of VDR in macrophages, dendritic cells and activated T and B lymphocytes, vitamin D has been suggested to play a role in modulating immune response [
15]. Therefore, we hypothesized in the first study that higher serum total 25(OH)D levels would be accompanied by some changes in the FA profile of the PBMC. The vitamin D group successfully increased their vitamin D status after four weeks of vitamin D3 supplementation, as compared to the control group not receiving vitamin D. However, similarly to the biochemical markers, no significant changes in the FA profile of the PBMC were observed, presumably due to the short length of the intervention. Nevertheless, some significant correlations were observed between FA PBMC content and metabolic biomarkers. Two inflammatory markers, hsCRP and IL-6, had a strong positive association with stearic acid (C18:0), but not palmitic acid (C16:0). Generally, exposure to palmitic acid is associated with its proinflammatory effect on variety of cells [
23,
24]. It has also been previously reported that C18:0 from PBMC phospholipids was negatively correlated with IL-6 production after inflammatory stimulus [
10]. In our study, the results of the association of PBMC FA content with plasma inflammatory markers showed the opposite, but this was observed based on non-stimulated PBMC metabolome and plasma biomarkers levels in healthy subjects. In addition, two other individual SFAs had a positive association with resistin and leptin, which are known as proinflammatory adipokines [
25,
26]. SFAs possess more proinflammatory functions than unsaturated FA [
27]. Adiponectin, in contrast, regarded as an anti-inflammatory adipokine that is generally reduced in obesity [
28], was also positively related to the C18:0 and SFA of PBMC. However, a recent study found that adiponectin can induce proinflammatory functions of isolated macrophages and T-cells [
29]. Nevertheless, since we did not observe in this study any differences in serum inflammatory markers, as well as the arachidonic acid content of PBMC, we cannot extrapolate the above findings to inflammatory functions following increased vitamin D intake. The release of arachidonic acid followed by the eicosanoid production pathway is the main characteristic of inflammation processes [
30].
In the second study, we employed an additional group of younger adults to see if it is possible to expand the profiling of PBMCs to include AA profiling, as well as to test the difference in the metabolite profile of PBMC between genders. Females and males differ in adipose tissue content and distribution, as well as body protein stores [
31], which could provoke different FA and AA footprints of the PBMC. However, after controlling for multiple comparisons, only isoleucine significantly differed between genders. Because there was a significant difference in BMI between the genders, we subsequently controlled the statistical analyses for BMI and observed that there were no significant difference between the groups. To our knowledge, this is the first report of the AA content in PBMC. The role of different AAs in cells has been extensively studied. While glutamine plays a major role in the metabolism of immune system cells [
32], other AAs have important regulatory functions by affecting protein synthesis, the production of cytokines and other immune functions. Aspartic acid plays an important role in the production of NO through ciruline recycling and is crucial for cell proliferation in response to immunological challenges. Branched Chain Amino acids (BCAAs), including valine and isoleucine, are the essential AA involved in protein synthesis through their action on the mTOR signalling pathway [
33] and were found in the second study to be higher in the PBMCs of persons with higher BMI or confounded by BMI in the between genders comparison. Indeed, BCAAs have been shown to be elevated in plasma of obese subjects and contribute to obesity-induced insulin resistance [
34].
The present studies have limitations and strengths. The major strength of our study was that the metabolic profiling of PBMCs was combined with extensive blood biochemical analysis, which could give a broad overview of PBMC function in response to FA metabolism and inflammation. In the second study, for the first time, both aqueous (AA) and organic (FA) extracts were analysed, illustrating the overall metabolic profile of PBMCs in a steady, fasting condition, and highlighting the possible differences between BMI rank. The limiting factors include low numbers of subjects; however, this study was set in order to prove the application of PBMC in metabolomic research and not for hypothesis-based purposes. Due to the low number of subjects and the limited power of the study to detect significant differences, the results have to be interpreted with caution. Another limitation of the study is the fact that the PBMC cells include many cell types with different properties regarding their function. Nonetheless, the present study is an important demonstration of the feasibility of applying metabolomics analysis to PBMCs. Further work could be directed at applying this methodology to different isolated blood cell types, which would make biological interpretation of the results easier.