Keywords
Ramadan fasting - dopamine - saliva - interleukins - ELISA
Introduction
Intermittent fasting has garnered significant attention in recent years due to its
potential impact on various physiological and metabolic processes, including alterations
in neurotransmitter levels and inflammatory responses.[1] Among the neurotransmitters affected by intermittent fasting, dopamine (DA) holds
particular significance, given its crucial role in regulating mood and motivation.[2] Abnormalities in DA signaling have been implicated in mood disorders such as depression,
bipolar disorder, and addiction.[2] Understanding the changes in DA levels induced by fasting could provide valuable
insights into its potential therapeutic effects on mood-related conditions.[2]
Intermittent fasting has been associated with numerous health benefits beyond mood
regulation. Prior studies demonstrated improvements in insulin sensitivity, lipid
metabolism, gut microbiota health, and reduced inflammation and blood pressure among
individuals practicing intermittent fasting.[3] The potential anti-inflammatory effects of intermittent fasting, particularly during
practices such as Ramadan fasting, have shown promise in alleviating inflammatory
conditions such as rheumatoid arthritis.[4] However, a recent review reported that intermittent fasting has little or no effect
on key inflammatory markers.[5]
Inflammatory cytokines play an important role in maintaining neuronal integrity and
managing neurotransmitter systems including DA release in the brain. There is mounting
interest regarding their role in the onset of several behavioral alterations, with
the excess presence of inflammatory cytokines regarded as the primary cause for alterations
in DA secretion.[6] However, the impact of intermittent fasting on inflammatory cytokine secretion and
its subsequent effects on DA levels is largely elusive, especially considering that
the levels of these inflammatory cytokines are transient. Regarding the impact of
intermittent fasting on inflammatory cytokine, some studies suggest significant reductions
in proinflammatory markers,[7]
[8] while others report limited effects.[5] Discrepancies in findings may stem from variations in fasting protocols, sample
sizes, study samples, and design, highlighting the need for further research, particularly
well-powered randomized controlled trials, to elucidate the mechanisms underlying
these effects.
Saliva, as a biological fluid, offers a noninvasive and easily accessible means for
elucidating cytokine and neurotransmitter levels.[9] The close relationship between the salivary glands and the nervous system makes
the secretions from these glands a valuable source of biomarkers, including normal
and pathological conditions of the nervous system.[10] The use of salivary biomarkers presents several advantages, including cost-effectiveness,
ease of sample collection, and repeatability, making it a valuable alternative method.[11] However, there is limited research identifying transient changes in salivary biomarkers
influenced by intermittent fasting. Comparative studies and evaluations of the clinical
relevance of these biomarkers are necessary to enhance the use of saliva as a noninvasive
diagnostic tool. In this context, the present study aims to comprehensively investigate
changes in salivary levels of inflammatory cytokines and DA before and after Ramadan
fasting among young university students. By employing a noninvasive and objective
approach to sample collection, this study seeks to address existing gaps in the literature
regarding the detection of salivary biomarkers and their potential alterations following
intermittent fasting. Furthermore, the inclusion of dental students as a study population
offers a unique opportunity to explore the effects of fasting on individuals undergoing
academic stress, which may impact both their mental and physical well-being. This
study is particularly novel in its use of saliva samples, as prior studies have predominantly
utilized blood samples or animal models, thus providing new insights into young students'
physiological and psychological responses to fasting.
Materials and Methods
Population and Study Design
The current observational study collected data at a single point of time using a cross-sectional
quantitative methodology. Forty-four young healthy fasting participants (22 females
and 22 men) who were all students enrolled in the College of Dental Medicine at the
University of Sharjah were recruited in the study. Informed written consent was obtained
from all the study participants, and the design and nature of the study were also
detailed. The participants were requested to complete the Patient Health Questionnaire
(PHQ)-9 and Depression Anxiety Stress Scales questionnaires during saliva sample collection
(both before fasting and at the end of fasting). The study procedure was approved
by the University of Sharjah's Research Ethics Committee (REC-22-03-21-03-S) by national
and international norms and the Declaration of Helsinki.
Inclusion criteria were the following: young participants in good oral health who
fasted for 21 consecutive days for 13 hours (from 5 a.m. to 6:30 p.m.). Clinical evaluation
procedures included an absence of calculus, active caries, tooth brushing twice per
day, and maintaining good oral hygiene. We excluded subjects having a history of drug
abuse, eating disorders, malnutrition, diabetes, hypertension, renal impairment, and
neurological or mental diseases. Also, smokers and subjects taking any drugs that
might influence salivary flow were excluded from the study.
Saliva Collection
This observational study aimed to quantify cytokine and DA levels in saliva before
and after fasting for 21 consecutive days for 13 hours (from 5 a.m. to 6:30 p.m.).
Saliva samples were collected twice, the first sample was collected a day before fasting,
and the second sample at 3 weeks following the fasting period. The collection time
of both samples was between 11 a.m. and 1 p.m. Passive drooling was followed for saliva
collection. Participants were instructed to be seated with heads tilted forward, allowing
saliva to pool naturally in the mouth and 5 mL of unstimulated whole saliva was collected
from each participant for 10 minutes in sterile test tubes, labeled with a unique
identification number. The samples were transported immediately to the laboratory
in ice storage boxes. The saliva samples were further centrifuged at 2,500 rpm for
5 minutes to reduce multiple freeze-thaw cycles and remove cell debris and mucus contamination,
aliquoted and stored at −80°C freezer until the required number of samples (n = 40) was achieved. On the day of the multiplex and ELISA analysis, saliva samples
were further thawed in ice, centrifuged at 10,000 g for 10 minutes at 4°C, and supernatants
were collected for use in the study.
Cytometric Bead Array for the Estimation of Cytokine Levels in the Saliva Samples
Cytometric bead array was performed to determine the levels of the cytokines in the
saliva samples using the LEGENDplex Human Inflammation Panel 1 (13-plex) (Cat. no.:
740809; BioLegend, San Diego, California, United States). The kit quantifies the level
of cytokines including interleukin (IL)-1β, interferon (IFN)-α2, IFN-γ, tumor necrosis
factor (TNF)-α, monocyte chemoattractant protein (MCP)-1, IL-6, C-X-C motif chemokine
ligand 8 (IL-8), IL-10, IL-12p70, IL-17A, IL-18, IL-23, and IL-33 in the saliva samples.
The standard graphs and the experimental protocol were performed according to the
manufacturer's guidelines. Briefly, 25 μL of the saliva sample mixed with equal volumes
of assay buffer was incubated with the 25 μL microbeads for 2 hours in the dark with
mild rotation (800 rpm). The samples were washed with 350 μL 1x wash buffer and centrifuged at 2,000 rpm for 5 minutes. The supernatant was carefully
removed and the pellet was resuspended in 25 μL of the detection antibodies and further
incubated for 1 hour at room temperature (with mild shaking at 800 rpm). After incubation,
25 μL of the streptavidin–phycoerythrin was introduced subsequently to the standards
and test samples and incubated further for 30 minutes. The samples were then washed
with 350 μL wash buffer and centrifuged at 2,000 rpm for 5 minutes. The supernatant
was carefully removed and the pellet was resuspended in 200 μL wash buffer. The samples
were then acquired on a flow cytometer (BD Cytoflex, BD Biosciences, United States)
and analysis was performed by using LEGENDplex Data Analysis Software (BioLegend).
ELISA Analysis for Estimation of Salivary Dopamine Levels
Detection of DA levels in the saliva samples was performed using a human DA ELISA
kit (Cat. no.: E-EL-0046; Elabscience, United States). Briefly, 50 µL of saliva samples
were loaded into ELISA plates along with 50 µL of biotinylated detection antibody,
and the assay was performed according to the manufacturer's instructions. The samples
were incubated for 45 minutes at 37°C followed by washing with 1x wash buffer three times; 100 µL of horseradish peroxidase conjugate was further added
to each well and incubated for 30 minutes at 37°C. The ELISA plate was then washed
five times and 90 µL of substrate reagent was added and further incubated for 15 minutes
at 37°C. At the end of the incubation period, 50 µL of STOP solution was added and
absorbance read at 450 nm. A standard plot was prepared and the concentration of DA
in the study samples was extrapolated and interpreted in pg/mL.
Statistical Analysis
Data analysis was performed using SPSS (Statistical Package for the Social Sciences)
(Version 22, IBM Corp., United States). The descriptive statistics for continuous
data were reported as median and interquartile range (IQR) and for categorical data
as frequencies and percentages. Differences between pre- and postfasting were tested
using Wilcoxon's signed-rank test, depending on data normality. The Mann–Whitney's
U test was utilized to determine disparities in DA and cytokine levels across sex.
Simple and multiple linear regression analyses were performed to identify the factors
influencing the change in DA before and after fasting. Variables in the simple regression
model with a p-value less than 0.2 were included in the multiple regression model. Additionally,
correlation analysis was employed to explore the relationships between the change
in DA level before and after fasting and the change in cytokine level before and after
fasting. Correlation analysis was also performed between the change in DA level before
and after fasting and the change in mental health parameter scores before and after
fasting including stress, anxiety, depression, and PHQ. Bar graphs were generated
using Graph Pad PRISM (version 9.1.1). A p-value of less than 0.05 was considered statistically significant.
Results
The study participants (n = 44) were United Arab Emirates residents and young adults of age between 18 and
24 years. The median age of enrolled participants was 22 (2) and their median body
mass index (BMI) was 23.40 (6.23). No difference in BMI was observed among the male
and female participants. The participants completed a multicomponent questionnaire
related to their sociodemographic and mental health status including anxiety, depression,
and severity of depression.
Fasting Enhanced Salivary Proinflammatory Cytokine Levels
The findings of Wilcoxon's signed-rank test conducted to investigate the difference
in salivary cytokine levels before and after fasting are presented in [Table 1]. Interestingly, a statistically significant increase in certain key proinflammatory
cytokines such as IL-1β, TNF-α, IL-23, IL-33, and IL-8 was noted. Additionally, IFN-α2
levels were also significantly enhanced after fasting. There was significant increase
in IL-1β scores from before fasting (median [IQR]: 396.16 [721.00] vs. after fasting
569.45 [882.00]), with a p = 0.013. Similar findings were observed in the following cytokines (before fasting
vs. after fasting), such as IFN-α2: 0.25 (0) versus 0.38 (0), p = 0.010; TNF-α: 10.24 (18) versus 18.61 (18.00), p = 0.040; and IL-8: 1,373.34 (1,425.00) vs. 1,966.21 (1,636.00), p = 0.010. Furthermore, a highly significant increase (p < 0.001) was observed in IL-23 and IL-33 levels (before vs. after fasting) with the
median (IQR): 8.72 (9.00) versus 13.88 (10.00) and 3.20 (6.00) versus 9,10 (11.00),
respectively.
Table 1
Impact of fasting on salivary levels of pro- and anti-inflammatory cytokines
|
Variables
|
Median (IQR)
|
p-Value
|
|
Before fasting
|
After fasting
|
|
IFN-γ
|
2.52 (6.00)
|
3.74 (5.00)
|
0.253
|
|
IL-1β
|
396.16 (721.00)
|
569.45 (882.00)
|
0.013[a]
|
|
IFN-α
|
0.25 (0)
|
0.38 (0)
|
0.010[a]
|
|
TNF-α
|
10.24 (18.00)
|
18.61 (18.00)
|
0.040[a]
|
|
MCP-1
|
449.65 (459.00)
|
491.52 (486.00)
|
0.779
|
|
IL-23
|
8.72 (9.00)
|
13.88 (10.00)
|
<0.001[a]
|
|
IL-33
|
3.20 (6.00)
|
9.10 (11.00)
|
<0.001[a]
|
|
IL-18
|
754.62 (1,080.00)
|
1,005.00 (1,295.00)
|
0.084
|
|
IL-17
|
0.10 (0)
|
0.10 (0)
|
0.987
|
|
IL-12
|
1.37 (6.00)
|
2.31 (3.00)
|
0.359
|
|
IL-10
|
3.56 (7.00)
|
4.63 (8.00)
|
0.064
|
|
IL-8
|
1,373.34 (1,425.00)
|
1,966.21 (1,636.00)
|
0.010[a]
|
|
IL-6
|
8.35 (10.00)
|
10.06 (12.00)
|
0.076
|
Abbreviations: IFN, interferon; IL, interleukin; IQR, interquartile range; MCP, monocyte
chemoattractant protein; TNF, tumor necrosis factor.
a
p-Value is significant at 0.05.
On the other hand, there was no significant difference in the expression of the anti-inflammatory
cytokine IL-10 before and after fasting. This indicates that fasting had a statistically
significant impact on increasing salivary proinflammatory cytokine levels ([Table 1] and [Fig. 1]).
Fig. 1 Flow cytometry-based analysis of human salivary cytokines. The quantification and
comparative analysis of cytokines in the salivary samples was assessed by a bead-based
immunoassay on a flow cytometer using LEGENDplex Human Inflammation Panel (13-plex).
*
p < 0.05 and ***
p < 0.001. IFN, interferon; IL, interleukin; MCP1, monocyte chemoattractant protein
1; TNF-α, tumor necrosis factor α.
We observed a statistically significant difference in the median scores of nine proinflammatory
cytokines in saliva samples collected before fasting between females and males. Overall,
females had significantly higher levels of cytokines compared with males before fasting.
These cytokines include IFN-α (males vs. females): 0.13 (0) versus 0.33 (0) before
fasting, p < 0.001; TNF-α: 9.12 (13) versus 18.64 (21), p = 0.046; MCP-1: 331.74 (480) versus 578.71 (763), p = 0.031; IL-23: 7.63 (8) versus 11.85 (16), p = 0.012; IL-33: 1.70 (5) versus 5.30 (15), p = 0.004; IL-12: 0.77 (1) versus 2.29 (7), p = 0.012; IL-10: 1.63 (4) versus 4.68 (12), p = 0.005; IL-8: 1,171.36 (1,616) versus 1,544.33 (1,235), p = 0.037; and IL-6: 4.83 (10) versus 9.57 (11), p = 0.039. However, there was no statistically significant difference in cytokine levels
among males and females after fasting ([Supplementary Table S1] [available in the online version only]).
Fasting Alters Salivary Dopamine Levels but Not Mental Health Parameters
The findings presented in [Table 2] indicate the results of the Wilcoxon's signed-rank test conducted to investigate
the difference in DA, and mental health parameters among the study participants before
and after fasting. The results indicate a significant decrease in DA levels, median
(IQR): 217.40 (309.88) before fasting versus 133.60 (196.41) after fasting with a
p-value of 0.016 ([Table 2] and [Fig. 2A]). However, no significant difference in DA levels across genders was noted ([Fig. 2B]). Similarly, no significant difference was detected in the mental health status
of the study participants before and after fasting ([Table 2]).
Fig. 2 Comparison of median salivary dopamine scores before and after fasting. (A) The median scores of salivary dopamine altered significantly before and after fasting
among the study participants by the Wilcoxon's signed-rank test. (B) The median scores of salivary dopamine were comparable across genders before and
after fasting by the Mann–Whitney's U test.
Table 2
Impact of fasting on salivary DA and mental health
|
Median (IQR)
|
p-Value
|
|
Before fasting
|
After fasting
|
|
DA
|
217.40 (309.88)
|
133.60 (196.41)
|
0.016[a]
|
|
Stress
|
3.00 (3)
|
3.00 (3)
|
0.168
|
|
Anxiety
|
3.00 (3.75)
|
2.50 (3)
|
0.286
|
|
Depression
|
4.00 (3)
|
3.00 (2)
|
0.860
|
|
PHQ
|
9.00 (6.75)
|
8.00 (4)
|
0.720
|
Abbreviations: DA, dopamine; IQR, interquartile range; PHQ, Patient Health Questionnaire.
a
p-Value is significant at 0.05.
Factors Influencing Changes in Dopamine Levels (before and after Fasting)
[Table 3] shows the results of the multiple regression analysis performed to examine the influence
of the change in specific cytokines and the PHQ scores before and after fasting on
the change in the DA level (before and after fasting). It was observed that cytokines
such as IFN-α2 (p = 0.021), TNF-α (p = 0.017), MCP-1 (p = 0.048), IL-33 (p = 0.030), and IL-10 (p = 0.010) showed a significant effect on the change in DA levels by simple linear
regression analysis ([Table 3]). For multiple regression analysis, 11 variables were included including the cytokines
with a p-value less than 0.2 in simple linear regression. However, the study revealed an insignificant
relationship between these variables and the change in DA levels (before and after
fasting).
Table 3
Multiple linear regression
|
Δ DA
|
Simple linear regression
|
Multiple linear regression
|
|
Β
|
95% CI
|
p-Value
|
Adj β
|
95% CI
|
p-Value
|
|
Δ IL-1β
|
−0.05
|
−0.11 to 0
|
0.057
|
0.04
|
−0.07 to 0.15
|
0.435
|
|
Δ IFN-α2
|
−175.14
|
−323.01 to −27.28
|
0.021[a]
|
51.51
|
−221.34 to 324.36
|
0.703
|
|
Δ TNF-α
|
−3.89
|
−7.05 to −0.72
|
0.017[a]
|
−4.14
|
−10.79 to 2.51
|
0.213
|
|
Δ MCP-1
|
−0.06
|
−0.13 to 0
|
0.048[a]
|
−0.09
|
−0.21 to 0.04
|
0.166
|
|
Δ IL-23
|
−0.61
|
−1.40 to 0.18
|
0.126
|
0.05
|
−1.01 to 1.11
|
0.925
|
|
Δ IL-33
|
−4.52
|
−8.56 to −0.47
|
0.030[a]
|
−0.45
|
−7.93 to 7.03
|
0.903
|
|
Δ IL-17
|
−424.69
|
−979.49 to 130.10
|
0.130
|
−505.09
|
−1,129.50 to 119.32
|
0.109
|
|
Δ IL-12
|
−8.66
|
−20.31 to 3
|
0.141
|
3.30
|
−14.93 to 21.53
|
0.715
|
|
Δ IL-10
|
−7.61
|
−13.29 to −1.92
|
0.010[a]
|
−8.12
|
−17.74 to 1.51
|
0.095
|
|
Δ IL-6
|
−1.76
|
−4.76 to 1.23
|
0.242
|
3.45
|
−1.92 to 8.82
|
0.199
|
|
Δ PHQ
|
12.02
|
−5.52 to 29.57
|
0.174
|
14.08
|
−4.24 to 32.40
|
0.127
|
Abbreviations: Δ, difference before and after fasting; Adj β, adjusted β; CI, confidence
interval; DA, dopamine; IFN, interferon; IL, interleukin; MCP, monocyte chemoattractant
protein; PHQ, Patient Health Questionnaire; TNF, tumor necrosis factor; β, regression
coefficient.
Note: Determinants of changes in DA levels before and after fasting.
a
p-Value is significant at 0.05.
Correlation Analysis
The results of the correlation analysis are given in [Table 4]. The study revealed that the change in certain specific cytokine levels before and
after fasting is significantly correlated with the change in DA levels (before and
after fasting). Specifically, the findings showed a significant negative correlation
between the change in DA levels and the change in levels of IFN-α (r = − 0.346, p = 0.021); TNF-α (r = − 0.357, p = 0.017); MCP-1 (r = − 0.300, p = 0.048), IL-33 (r = − 0.328, p = 0.030), and IL-10 (r = − 0.385, p = 0.010) ([Table 4]).
Table 4
Correlation between changes in cytokine and mental health scores and changes in DA
levels before and after fasting
|
ΔDA
|
|
IFN-α
|
TNF-α
|
MCP-1
|
IL-23
|
IL-33
|
IL18
|
IL-17
|
IL-12
|
IL-10
|
IL-8
|
IL-6
|
Stress
|
Anxiety
|
Depression
|
PHQ
|
|
r
|
−0.346[a]
|
−0.357[a]
|
−0.300[a]
|
−0.234
|
−0.328[a]
|
−0.090
|
−0.232
|
−0.225
|
−0.385[b]
|
−0.090
|
−0.180
|
0.138
|
0.011
|
0.127
|
0.209
|
|
p-Value
|
0.021
|
0.017
|
0.048
|
0.126
|
0.030
|
0.562
|
0.130
|
0.141
|
0.010
|
0.562
|
0.242
|
0.371
|
0.943
|
0.412
|
0.174
|
Abbreviations: Δ, change in levels before and after fasting; DA, dopamine; IFN, interferon;
IL, interleukin; MCP, monocyte chemoattractant protein; PHQ, Patient Health Questionnaire;
r, correlation coefficient; TNF, tumor necrosis factor.
a
p-Value is significant at 0.05.
b
p-Value is significant at 0.01.
Discussion
The innate immune system plays a central role in controlling behavior through changes
in neurocircuitry and neurotransmitter systems in the brain.[12] This is partially due to the effect of inflammatory cytokines on monoamine neurotransmission.[13] DA is the key target of inflammatory cytokines, responsible for cytokine-induced
behavioral changes. To the best of our knowledge, this is the first study that comprehensively
assessed the effects of fasting on the levels of a panel of proinflammatory and anti-inflammatory
cytokines in saliva before and after Ramadan and correlated its effects on DA release,
mental health, and well-being of individuals.
The present study was conducted during Ramadan in United Arab Emirates among university
students. The results demonstrate that fasting during Ramadan significantly altered
salivary proinflammatory cytokine levels. We found a significant increase in the level
of proinflammatory cytokines such as IL-1β, TNF-α, IL-23, IL-33, and IL-8, while IL-10
levels remain unchanged. The observed increase in proinflammatory cytokines suggests
that fasting may induce an inflammatory response in the oral cavity, potentially as
a physiological reaction to dietary changes. This is in contrast to findings from
prior research. Tastemur et al reported that fasting during Ramadan decreased plasma
levels of proinflammatory cytokines (TNF-α, IL-8), heat shock protein 70, and oxidative
stress markers.[7] Similarly, a meta-analysis of 10 studies on individuals practicing fasting during
Ramadan showed a marginal decrease in inflammatory biomarkers while fasting.[8] Yet, another study reported a decline in circulating proinflammatory cytokines,
body fat, and leukocyte levels during Ramadan fasting indicating an attenuation of
the body's inflammatory status.[8] The discrepancy in data may be due to differences in study methodologies, such as
the use of blood and animal models and the median age of the participants. It is important
to note that in the present study, all participants recruited were young university
students. The alterations in energy provision and metabolic control linked to fasting
might elicit the body's reaction to fluctuations in nutrient accessibility,[14] which could potentially result in elevated concentrations of inflammatory cytokines,
as shown in our study.
Additionally, a baseline difference in cytokine levels between genders was noted,
with females exhibiting higher levels before fasting. Such a disparity may be due
to various biological factors, including hormonal differences, which are known to
influence immune responses.[15] However, after fasting, the difference in cytokine levels between males and females
is negligible suggesting that fasting may have normalized the variations in cytokine
production and potentially mitigated the initial gender-based differences. The current
study also showed that there was no significant change in the levels of the anti-inflammatory
cytokine IL-10, indicating that the inflammatory response was not counterbalanced
by anti-inflammatory mechanisms in the oral cavity.
Fasting alters reward-related behaviors and decreases baseline DA levels.[16] Also, several innate immune cytokines such as IFN-α is reported to produce high
rates of behavioral disturbances, including depression and fatigue.[17] DA is involved in multiple behaviors, including feeding, and chronic fasting is
known to affect DA neural circuits significantly due to a reduction in food intake
and associated body weight. Previous research has also explored various aspects of
DA regulation, its impact on metabolic programming, and immune responses.[18] Also, the impact of DA signaling on motivation, decision-making, and reward processes.[19] However, the effects of short-term changes in food intake, such as acute fasting,
affecting DA circuits are not much explored.
Interestingly, in the current study, a significant decrease in salivary DA levels
after fasting was noted. The change in DA levels, however, did not correspond to changes
in mental health parameters such as anxiety, depression, and severity of depression
during the short time frame of the study. This finding suggests that while fasting
alters neurochemical markers such as DA, it does not significantly affect self-reported
mental health status of the participants. The reduction in DA could be indicative
of changes in reward- and stress-related pathways, which may be influenced by dietary
intake and fasting.[16] The lack of change in mental health status despite changes in cytokine and DA levels
could be attributed to the fact that the physiological stress of fasting does not
immediately translate to perceivable changes in mental health,[20] given that the study was for a short period.
Further in the study, we observed that cytokines such as IFN-α2, TNF-α, MCP-1, IL-33,
and IL-10 showed a significant effect on the change in DA levels by the simple linear
regression analysis. However, when included in a multiple regression model, none of
these cytokines significantly predicted the change in DA levels. This could also be
attributed to the short duration of the fasting period, and long-term studies could
provide more comprehensive insights into the collective effect of these cytokines
on DA release. However, significant negative correlations between changes in DA levels
and changes in levels of IFN-α2, TNF-α, MCP-1, IL-33, and IL-10 were observed. This
inverse relationship implies that as levels of these cytokines increase, DA levels
tend to decrease, highlighting a potential link between inflammatory processes and
DA regulation.
The current study is limited owing to a single study sample, as saliva samples were
collected exclusively from university students who are typically under stress. Additionally,
our study was conducted on a sample of students enrolled in one institute, which may
limit its generality to a broader population. Finally, the mental health was evaluated
based on self-reported questionnaires.
Conclusion
In conclusion, the current study demonstrates that fasting during Ramadan significantly
alters salivary proinflammatory cytokine levels and DA release in youths. The mental
health status of these young participants, however, remains unaffected in this short
time frame of the study. The study highlights complex interactions between fasting,
immune response, and neurochemical changes, warranting further research to explore
the underlying mechanisms and long-term collective effects of the inflammatory cytokines
on DA release and overall well-being. Correlations were identified between changes
in DA levels and changes in levels of cytokines and chemokines such as IFN-α2, TNF-α,
MCP-1, IL-33, and IL-10 before and after fasting. Overall, the potential predictive
value of these associations as indicators of dopaminergic responses to fasting and
the mechanisms underlying these associations are suggested based on our study findings.
