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Journal of Migration and Health logoLink to Journal of Migration and Health
. 2026 Sep 14;14:100442. doi: 10.1016/j.jmh.2026.100442

Understanding stress through metabolomic and psychosocial lenses: Pathways to biomarker discovery

Fatin Atrooz a, Ruba A Zenati b,c, Mohammad H Semreen b,c,⁎⁎, Karem H Alzoubi d, Hamza M Al-Hroub c, Yasser Bustanji c,e,f, Omar F Khabour f, Sally Aljararwah f, Samina Salim a,⁎
PMCID: PMC13628689  PMID: 42825033

Abstract

Identifying reliable biomarkers of trauma-related psychological stress is critical for accurate diagnosis and appropriate intervention. Metabolomic profiling offers a promising approach to uncover biochemical correlates of stress. This study investigated salivary metabolomic signatures of traumatic stress in Syrian refugee women resettled in Jordan, with Jordanian women serving as a comparison group. We conducted a cross-sectional study to assess mental distress among Syrian refugee (n = 48) and Jordanian women (n = 52) living in northern Jordan. Saliva samples were collected and processed from all participants, of which 25 (11 Syrian refugee and 14 Jordanian women) yielded sufficiently detectable metabolomic profiles and were included in the exploratory metabolomic analysis. Psychometric assessments included validated measures of perceived stress and mental distress. Saliva samples were analyzed using global quantitative metabolomics via high-resolution TIMS-TOF mass spectrometry to identify metabolites associated with stress. While Syrian refugee women reported higher perceived stress compared with Jordanian women (mean ± SD: 30.72 ± 9.2 vs. 27.19 ± 7.7; p = 0.040), both Jordanian and Syrian women exhibited high scores in Self Reporting Questionnaire (mean score ± SD: Syrian refugees = 11.59 ± 4.5, Jordanian women = 10.60 ± 4.7; p = 0.285). Syrian refugee women exhibited elevated salivary metabolites linked to oxido-inflammatory and stress-response pathways including purine metabolism, glutathione metabolism, pyrimidine metabolism, and plasmalogen synthesis. Our findings point to salivary metabolites involved in oxido-inflammatory cascades as potential biomarkers of psychological stress, which in the future may provide objective, noninvasive indicators of stress, complementing psychometric assessments and offering new avenues for evaluating mental health risk in vulnerable populations such as refugees. Findings should be interpreted as associations rather than evidence of causality.

Keywords: Health disparities, Mental health, Syrian refugees, Jordan, Stress, Metabolomics, Oxidative stress

1. Introduction

Mental disorders are among the most common health conditions worldwide. According to the World Health Organization (WHO) 2022 Report, approximately one in eight people globally, that is, >970 million individuals are affected with a mental disorder. (McGrath et al., 2023). Despite their high prevalence, >70% of people with mental disorders receive no treatment, especially in low- and middle-income countries like Jordan (Alloh et al., 2018; Gearing et al., 2013; Murray and Jordans, 2016; Patel et al., 2007). Even in high-income countries, mental health services are often under-resourced, and stigma remains a major barrier to seeking help (Al-Soleiti et al., 2021; Al Ali et al., 2017). The situation is worse for at-risk communities such as the refugee groups (Kiselev et al., 2020; Shannon et al., 2015).

It is well known that war and conflict have produced a high burden of mental distress among the 27 million forcibly displaced groups, who are up to ten times more likely to be diagnosed with mental illnesses such as Post Traumatic Stress Disorder (PTSD) than the general population (Javanbakht et al., 2018). The Syrian war is considered as one of the world’s most complicated humanitarian crises in modern history (Berti, 2015; Gabiam, 2016; Tateyama, 2018), although this might change considering the most recent Russain-Ukrainian and Israel-Hamas conflicts which have resulted in a major humanitarian crisis in both Ukraine and Gaza (Salim, 2024). Syrians are one of the largest forcibly displaced populations in the world, 13 million of whom have fled to Turkey, Lebanon, Iraq, Jordan, and Egypt (Faleh and Ahmad, 2018). In our recently published studies (Atrooz et al., 2023, 2024), Syrian refugee women reported significantly high mental distress than men. Although high mental distress was reported among the refugee women, whether they suffered from mental illnesses such as PTSD was unclear. Identifying biochemical changes associated with mental distress is likely to offer useful insights into the mental health status and will inform intervention. This is critical as at present diagnosis of mental disorders is derived solely from clinical impressions based on the Diagnostic and Statistical Manual of Mental Disorders 5 (DSM-5) or the International Statistical Classification of Diseases and Related Health Problems 10th Revision (ICD-10) (Paniagua, 2018) which limits the ability to prescribe a customized treatment. Therefore, there is a pressing need for the development of biomarkers that could help improve diagnosis, and facilitate intervention development for better patient outcomes.

Metabolomics has emerged as a powerful systems biology approach for elucidating molecular alterations underlying complex phenotypes (Sethi and Brietzke, 2016). Because metabolites represent the ultimate downstream products of genomic, transcriptomic, and proteomic regulation, they provide a highly sensitive readout of dynamic physiological states and their dysregulation in disease (Guest et al., 2016; Sethi and Brietzke, 2016). High resolution metabolite profiling enables the detection of subtle biochemical disturbances that precede clinical manifestations, thereby offering a rational framework for developing predictive biomarkers capable of informing early interventions (Kaddurah-Daouk et al., 2008).

Psychological distress represents a state of sustained allostatic load characterized by dysregulation of the hypothalamic–pituitary–adrenal (HPA) axis, chronic activation of oxido-inflammatory pathways, and disruption of neuroendocrine–immune communication (Mellon et al., 2018; von Majewski et al., 2023). These processes converge on core metabolic networks, including nucleotide turnover, glutathione-dependent redox buffering, and phospholipid remodeling, all of which are highly susceptible to redox imbalance and inflammatory signaling (Li et al., 2025). In this context, salivary metabolomics provides a non-invasive and physiologically relevant biospecimen for assessing stress-related metabolic status. Saliva reflects both systemic biochemical changes and local oropharyngeal physiology, making it an attractive matrix for biomarker discovery. Accordingly, the present study investigated the salivary metabolic profile of Jordan-based Syrian refugee women. Samples from Jordanian host community women were used for comparative analysis. No specific metabolic pathways were hypothesized a priori because untargeted metabolomics was employed. By integrating psychometric assessments with untargeted metabolomic profiling, this work sought to identify metabolic pathways associated with psychological distress in an exploratory manner, with two prime objectives; one of advancing mechanistic understanding and second, shedding light on the candidate salivary biomarkers of psychological distress. Overall goal was to integrate psychosocial measures with metabolomic profiling to identify biological correlates associated with elevated psychological distress. Our goal was not to replace clinical diagnosis but to explore candidate biomarkers that may complement existing assessment approaches and improve understanding of stress-related biological processes. To our knowledge, only a few studies have examined metabolomic signatures of psychological distress in refugee populations, highlighting an important gap in understanding the biological correlates of trauma-related mental health in displaced communities.

2. Methods

This is a cross sectional study conducted in an urban area of nothern Jordan between July and October 2022. The study was approved by the Institutional Review Board (IRB) Committee for the Protection of Human Subjects, University of Houston (UH), Houston, TX (approval code STUDY00002929), and by the Jordan University of Science and Technology (JUST) IRB, Irbid, Jordan (IRB#52/148/2022, #10.05.2022, #10.30.2024).

2.1. Subject recruitment

Syrian refugees resettled in northern Jordan and Jordanian women living in the same urban areas were recruited using snowball sampling. The basic criteria of inclusion included adult Syrian refugee or Jordanian women (18 years or older). The research team at JUST described the study objectives to the participants before obtaining study participation consent. All participants provided written informed consent prior to participation, including specific consent for saliva collection and metabolomic analysis. The consent forms clearly described the study objectives and procedures, including psychometric assessments and characterization of salivary metabolomic profiles. All identification data was replaced with codes and stored on a password protected secure server (institutional REDCap).

2.2. Online surveys

The Arabic versions of the survey questionnaires were uploaded on the UH-REDCap platform for secure survey management and data collection. The students accessed the survey via REDCap and obtained the participant consent electronically. Participants were provided the option to complete the survey either independently or with one-on-one guidance from study team, who were available to offer any explanations/clarifications if/when needed by the participants. Upon survey completion, each participant received a $7 (5 Jordanian Dinars) gift card. Surveys included a sociodemographic questionnaire with general questions on the demographic and socioeconomic circumstances including age, education level, relationship status, number of children, and family members, health insurance status, employment status, and average monthly income. Questions related to prevalence of chronic diseases including diabetes, hypertension, hypothyroidism, asthma, and irritable bowel syndrome were included in the demographic characteristics section of the survey, in addition to body-mass index measures including weight and height.

Measures of perceived stress, and mental distress included validated Arabic versions of the Perceived Stress Scale (PSS) and Self-Reporting Questionnaire (SRQ), respectively. The PSS is a global measure of perceived stress (Cohen et al., 1983), it consists of 7 positive items, which represent the coping ability subscale, and 7 negative items, which represent perceived stress. Each item is rated on a 5-point scale (0 = Never, 1 = Almost Never, 2 = Sometimes, 3 = Fairly Often, 4 = Very Often). The total score was calculated by adding up scores for all items after reversing the scores for the negative items. The Arabic version of the PSS-14 has been previously validated (Almadi et al., 2012; Atrooz et al., 2022). The PSS-14 showed adequate reliability in our sample, with a Cronbach’s alpha coefficient of 0.78.

The SRQ is an instrument developed by the World Health Organization to screen for mental disorders, including depression, anxiety-related disorders, and somatoform symptoms (Beusenberg et al., 1994). In this study, we used the short form of the SRQ (SRQ-20), which consists of the first 20 non-psychotic items, each item is scored 1 or 0: a score of 1 indicates that the symptom was present during the past month; a score of 0 indicates that it was absent. The total score was calculated by adding up the score for each item, the range for total score is 0–20, the score of 7 is considered the clinical cutoff for the presence of a potential psychological disorders. The items in the SRQ were further classified into two subscales as described previously (Idaiani et al., 2021). Subscale 1 describes depression symptoms, while subscale 2 describes symptoms of anxiety (Atrooz et al., 2023). This instrument was previously validated in the Arab population (Al-Subaie et al., 1998; El-Rufaie and Absood, 1994). The instrument demonstrated excellent reliability in our sample, with a Cronbach’s alpha value of 0.84.

2.3. Saliva collection

Saliva samples were collected from study participants in saliva collection tubes using swabs (#5001.02 −.05 Salimetrics, USA). Saliva samples were centrifuged at 15,000 rpm for 15 min at 4 C°, then stored at −80 C°. The samples were coded for privacy and used for metabolomic analysis.

2.4. Statistical analysis

Using descriptive statistics, we conducted sample comparisons between Syrian and Jordanian women using independent t-test or chi-square test for continuous and categorical variables, respectively. All analyses were conducted using IBM SPSS (V 29.00, Armonk, NY: IBM Corp). Significance was set at p < 0.05.

2.5. MS-based quantitative shotgun metabolomics analysis

For metabolomic extraction, saliva samples were supplemented with 400 µL of lysis buffer containing protease inhibitors (one tablet dissolved in 10 mL) (Zenati et al., 2023). After a 10 min incubation period, samples were vortex mixed for 2–4 min. Subsequently, 400 µL methanol and 300 µL chloroform were added, vortexed again and centrifuged at 14,000 rpm for 5 min. The resulting upper phase, containing the metabolites, was carefully transferred into glass vials. To enhance metabolite recovery, 400 µL of methanol was added to the remaining phase, vortexed, centrifuged again, and the supernatant was pooled with the initial extract. The combined extract was then dried under vacuum. The dried metabolite extracts were reconstituted in 200 µL of 0.1% formic acid in water and analyzed by UHPLC-QTOF MS.

Metabolite detection was carried out using an Elute UHPLC system coupled to a high-resolution Q-TOF mass spectrometer (Bruker, Bremen, Germany), operated under standard conditions as previously published (Semreen et al., 2022; Sharaf et al., 2022). Prior to sample analysis, instrument performance was verified using the Bruker T-ReX LC-QTOF Solution. Reversed-phase liquid chromatography (RPLC) separation, mass accuracy, and multipoint retention time calibration were assessed using TRX-3112-R/MS Certified Human Serum for the Bruker T-ReX LC-QTOF Solution (Nova Medical Testing Inc.). External mass calibration was performed using sodium formate. A pooled QC sample was prepared by combining equal aliquots (10 µL) from each study sample and was injected at the beginning of the analytical run, at regular intervals throughout the analytical sequence, and at the end of the run to monitor instrument stability, chromatographic reproducibility, and analytical performance. QC performance was evaluated by calculating the relative standard deviation (RSD) of metabolite peak intensities across pooled QC injections. Only metabolites exhibiting an RSD < 30% were retained for downstream analyses. Batch correction was performed using the pooled QC samples to correct for analytical drift across the analytical sequence. Subsequently, metabolite intensities were normalized using median normalization prior to statistical analysis to minimize systematic variation and improve data comparability across samples. Data acquisition was performed in positive ionization mode using Auto MS/MS, with acquisition and fragmentation settings as previously optimized for global metabolomics analysis (Zenati et al., 2023). Data processing was performed in MetaboScape® 4.0 (Bruker) using the T-ReX 2D/3D workflow, and metabolite annotation was achieved by matching accurate mass, isotope patterns, retention time, and MS/MS spectra against HMDB 4.0. Candidate metabolite annotations were accepted using predefined quality criteria including a mass error < 5 ppm, an MS/MS score > 600, and a retention time deviation < 0.3 min. Annotation quality (AQ) scores generated by MetaboScape were used to prioritize the most reliable metabolite assignments. Metabolite identifications were assigned to MSI Level 2, as authentic reference standards were not available for all detected metabolites. Processed data were further analyzed in MetaboAnalyst 5.0 (www.metaboanalyst.ca), where statistical analyses (t-test, PCA, pathway enrichment, ROC analysis with top-ranked metabolites (5–100 variables), and hierarchical clustering) were performed with false discovery rate (FDR) correction. Metabolites with an adjusted p-value < 0.05 were considered significant.

3. Results

3.1. Sociodemographic characteristics of participants

Data were collected from a total of 100 Syrian refugee and Jordanian women (48 Syrian refugees women, 52 Jordanian women). The age of the participants was between 19–69 with average age of 42.82 ± 4.6. The age distribution was comparable between Syrian refugee and Jordanian women with around half of the participants in the age category groups of 40–59 (Table 1). The difference in education level between Syrian refugee and Jordanian women was significant, with >87% Syrian refugee women did not complete high school. Although the employment rate was higher among Syrian refugee women than Jordanian women, the reported monthly income was significantly lower among Syrian refugee women as compared to Jordanian women, data showed that 64% of Syrian refugee women reported monthly income of <250 Jordanian Dinar (JD) ($352) and the rest reported monthly income of 250–550 JD. Most of Syrian refugee women did not have health insurance which suggested that they do not have access to governmental health services in Jordan. The prevalece of chronic diseases was comparable between Syrians and Jordanians. Both Syrian refugee and Jordanian women reported high prevalence of cigarette and hookah smoking with rates of 13% and 17%, respectively. The BMI characterestics of women in both groups was similar with 38% of women within the over weight category and 38% of them within the obese categories (Table 1).

Table 1.

Sociodemographic characteristics and psychometric scores of Syrian refugee and Jordanian women.

Variable Jordanian Women N = 52 Syrian Refugee Women N = 48 Total N = 100 Statistics P-Value
N (%) N (%) N (%)
Age
18–25 5 (9.6) 7 (14.6) 12 (12.0) 0.643 0.887
26–39 13 (25.0) 12 (25.0) 25 (25.0)
40–59 30 (57.7 26 (54.2) 56 (56.0)
60+ 4 (7.7) 3 (6.3) 7 (7.0)
Marital Status
Single 4 (7.7) 3 (6.3) 7 (7.0) 1.676 0.795
Married 35 (67.3) 36 (75.0) 71 (71.0)
Seperated 2 (3.8) 1 (2.1) 3 (3.0)
Divorced 2 (3.8) 3 (6.3) 5 (5.0)
Widowed 9 (17.3) 5 (10.4) 14 (14.0)
Education
Less than High School 31 (59.6) 42 (87.5) 73 (73.0) 9.968 0.007⁎⁎
High School 12 (23.1) 4 (8.3) 16 (16.0)
College 9 (17.3) 2 (4.2) 11 (11.0)
Employment
No 46 (88.5) 35 (72.9) 81 (81.0) 3.919 0.048*
Yes 6 (11.5) 13 (27.1) 19 (19.0)
Monthly Income
<250 JD 18 (34.6) 31 (64.6) 49 (49.0) 13.835 0.008⁎⁎
250–550 JD 25 (48.1) 17 (35.4) 42 (42.0)
551–800 JD 4 (7.7) 0 (0.0) 4 (4.0)
801–1500 JD 3 (5.8) 0 (0.0) 3 (3.0)
>1500 JD 2 (3.8) 0 (0.0) 2 (2.0)
Health Insurance
No 15 (28.8) 45 (93.8) 60 (60.0) 43.810 <0.001⁎⁎⁎
Yes 37 (71.2) 3 (6.3) 40 (40.0)
Diabetes
No 43 (82.7) 40 (83.3) 83 (83.0) 0.007 0.932
Yes 9 (17.3) 8 (16.7) 17 (17.0)
Hypertension
No 41 (78.8) 41 (85.4) 82 (82.0) 0.730 0.393
Yes 11 (21.2) 7 (14.6) 18 (18.0)
Hyperthyrodism
No 50 (96.2) 47 (97.9) 97 (97.0) 0.26 0.606
Yes 2 (3.8) 1 (2.1) 3 (3.0)
Irritable Bowel Syndrome
No 43 (82.7) 40 (83.3) 83 (83.0) 0.007 0.932
Yes 9 (17.3) 8 (16.7) 17 (17.0)
Smoking Cigarettes
Never 45 (86.5) 42 (87.5) 87 (87.0) 0.020 0.886
Current Smoker 7 (13.5) 6 (12.5) 13 (13.0)
Waterpipe Use
No 42 (80.8) 41 (85.4) 83 (83.0) 0.382 0.536
Yes 10 (19.2) 7 (14.6) 17 (17.0)
Body Mass Index
Under weight (<18.5) 1 (1.9) 1 (2.1) 2 (2.0) 0.779 0.854
Normal (18.5–24.9) 13 (25.0) 9 (18.8) 22 (22.0)
Over weight (25–29.9) 20 (38.5) 18 (37.5) 38 (38.0)
Obese (>30) 18 (34.6) 20 (41.7) 38 (38.0)
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Data was analysed using Chi-square.

⁎

Significant at p < 0.05,. 

⁎⁎

Significant at p < 0.01,. 

⁎⁎⁎

Significant at p < 0.001.

3.2. Psychological measures

Mental distress of the participants was evaluated using SRQ and perceived stress was evaluated using PSS. Comparative mean analysis of the PSS score showed that Syrian refugee women exhibited higher score as compared to Jordanian women (mean score ± SD: Syrian refugees = 30.72 ± 9.2, Jordanian women = 27.19 ± 7.7; mean difference = 3.53, 95% CI: 0.156 to 6.906; p = 0.040), (Fig. 1A). Both Jordanian and Syrian women exhibited high scores in SRQ, above the clinical cut-off (mean score ± SD: Syrian refugees = 11.59 ± 4.5, Jordanian women = 10.60 ± 4.7; mean difference = 0.99, 95% CI: −0.840 to 2.821; p = 0.285), (Fig. 1B). Furthermore, 83% of Syrian refugee women (n = 40) and 77% of Jordanian women (n = 40) had SRQ scores above the clinical cutoff of 7; however, the difference between the groups was not statistically significant (χ² = 0.303, p = 0.582). Further analysis of SRQ subscales revealed that Syrian and Jordanian women exhibited comparable anxiety scores (mean score ± SD: Syrian refugees = 5.54 ± 2.1, Jordanian women = 5.54 ± 2.3; mean difference = 0.00, 95% CI: −0.880 to 0.887; p = 0.464) (Fig. 1C). For depression subscale, Syrian refugee women exhibited slightly higher scores as compared to Jordanian women (mean score ± SD: Syrian refugees = 5.81 ± 3.1, Jordanian women = 5.08 ± 2.8; mean difference = 0.73, 95% CI: −0.435 to 1.906; p = 0.300) (Fig. 1D).

Fig. 1.

Fig. 1

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Psychological measure scores of Syrian refugee and Jordanian women. (A) Perceived Stress Scale (PSS) total score, (B) Self-Reporting Questionnaire (SRQ) total score. (C) Self-Reporting Questionnaire- Anxiety subscale. (D) Self-Reporting Questionnaire- Depression subscale. Means are indicated for each group, whiskers represent minimum and maximum values. Data were analyzed using an independent t-test. * Significantly different at p < 0.05.

3.3. Metabolomic analysis

Of the 100 saliva samples collected and subjected to metabolomic analysis, 25 samples generated metabolomic profiles of sufficient analytical quality for downstream evaluation, comprising 11 Syrian refugee women and 14 Jordanian women. The remaining 75 samples were excluded from subsequent analyses because their processed datasets were characterized by predominantly zero or non-detectable metabolite signals, limiting their suitability for reliable downstream metabolomic analysis. Untargeted metabolomic profiling of all 100 saliva samples was performed using UHPLC coupled to a high-resolution TIMS-TOF mass spectrometer. A total of 146 metabolites were identified. Multivariate statistical analysis using sparse Partial Least Squares (sPLS) demonstrated a clear separation between the refugee and Jordanian women. The sPLS scores plot revealed distinct clustering of the two groups along Component 1, which explained 22.1% of the variance, while Component 2 accounted for 4.7% of the variance. The well-defined clustering patterns with minimal overlap between the groups indicate substantial differences in salivary metabolomic profiles, reflecting distinct metabolic signatures (Fig. 2A). The sPLS loading plot was used to identify the metabolites most strongly contributing to the discrimination between the two groups (Fig. 2B). The list of top contributors along Component 1 included the following; alloisoleucine, phenylalanine, homoserine, uridine 5′-monophosphate, glycyl-l-leucine, uracil, (R)-lipoic acid, isoleucine, 5-aminopentanoic acid, and aminocaproic acid. Heatmap color coding indicated that most of these metabolites were elevated in the Syrian refugee group when compared to the Jordanian women.

Fig. 2.

Fig. 2

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Multivariate analysis of salivary metabolomic profiles from Syrian refugee and Jordanian women using sparse Partial Least Squares (sPLS). (A) sPLS scores plot showing clear separation between Syrian refugee (green) and Jordanian (pink) women along Component 1 (22.1% variance) and Component 2 (4.7% variance). (B) sPLS loading plot displaying the top metabolites contributing to group separation along Component 1. Heatmap boxes on the right show metabolite abundance in each group: blue indicates low levels and red indicates high levels, following a blue–white–red gradient scale.

To evaluate the classification performance of the identified metabolites, ROC analysis was performed using different variable numbers (5–100 top-ranked features) (Fig. 3A). The area under the curve (AUC) values ranged from 0.78 for the top 5 metabolites to 0.855 for the top 25 metabolites, with corresponding confidence intervals indicating robust discriminative power. These results demonstrate that a relatively small subset of metabolites are distinguishable of Syrian refugee and Jordanian women, supporting their potential utility as diagnostic biomarkers. Significantly altered metabolites were identified using a Student’s t-test with an adjusted p-value < 0.05, yielding 20 dysregulated metabolites (Table 2), of which 19 were elevated and 1 was reduced in the Syrian refugee women (Fig. 3B). Elevated metabolites included amino acids and derivatives such as alloisoleucine; Fold Change (FC) = 3.74, isoleucine (FC = 4.30), tryptophan (FC = 2.47), and proline (FC = 2.75); nucleotide metabolites such as guanine (FC = 2.04), uridine 5′-monophosphate (FC = 2.52), cytidine monophosphate (FC = 2.84), and deoxyadenosine monophosphate (FC = 5.42); and organic acids/metabolic intermediates such as glutamic acid (FC = 2.11), and glucosamine 6-phosphate (FC = 2.16). Stearic acid (FC = 0.40) was the only metabolite found to be significantly downregulated.

Fig. 3.

Fig. 3

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Classification performance and differential abundance of salivary metabolites between Syrian refugee and Jordanian women. (A) ROC curves for classification models built using the top-ranked metabolites (5–100 variables). (B) Volcano plot of identified metabolites, showing log2 fold change (FC) versus −log10(p-value). Red-shaded metabolites indicate higher abundance in the Syrian refugee women, while blue-shaded metabolites indicate higher abundance in the Jordanian women. Circle sizes correspond to p-value thresholds, and the dashed lines represent statistical (adjusted p < 0.05) and fold-change cutoffs.

Table 2.

List of significantly altered metabolites between Syrian refugee and Jordanian women identified by untargeted UHPLC–QTOF metabolomics analysis of saliva samples.

Metabolite name Adjusted p-value log2(FC)* Fold Change (FC)
Alloisoleucine 0.001,831 1.9025 3.7386
Glycyl-l-leucine 0.008,859 2.5915 6.0273
Homoserine 0.008,859 1.8217 3.5351
Uridine 5′-monophosphate 0.008,859 1.3338 2.5206
Uracil 0.010,399 1.3168 2.4911
Isoleucine 0.012,475 2.1052 4.3026
5-Aminopentanoic acid 0.012,475 1.6538 3.1465
Aminocaproic acid 0.012,475 1.1333 2.1935
Tryptophan 0.017,872 1.3071 2.4744
Hypoxanthine 0.022,694 1.3017 2.4651
Glutamic acid 0.025,914 1.0784 2.1117
Cytidine monophosphate 0.027,581 1.5076 2.8433
Glucosamine 6-phosphate 0.027,581 1.1118 2.1612
Aspartyl-l-phenylalanine 0.031,233 2.2796 4.8554
Deoxyadenosine monophosphate 0.036,286 2.4394 5.4241
N6-Acetyl-l-lysine 0.036,286 1.2896 2.4447
Proline 0.038,896 1.4586 2.7485
Pyrrolidonecarboxylic acid 0.039,085 1.0755 2.1074
Guanine 0.046,668 1.0311 2.0436
Stearic acid 0.049,749 −1.3165 0.4015
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Fold change (FC) values >1 indicate higher abundance in the Syrian refugee group, while FC < 1 indicates lower abundance compared to Jordanian women. Metabolites were selected based on Student’s t-test with adjusted p < 0.05.

The 20 significantly altered metabolites were further used for pathway enrichment analysis. This highlighted four significantly dysregulated metabolic pathways: Purine metabolism (p = 0.0148), Glutathione metabolism (p = 0.0298), Pyrimidine metabolism (p = 0.0406), and Plasmalogen synthesis (p = 0.0487) (Fig. 4). The pathway mapping status of all significantly altered metabolites, including HMDB, PubChem, KEGG identifiers, and mapping status, is provided in Supplementary Table S1, while the metabolite–pathway membership matrix is shown in Supplementary Figure S1. In purine metabolism, the enriched metabolites included guanine, glutamic acid, hypoxanthine, and deoxyadenosine monophosphate, suggesting alterations in nucleotide turnover and salvage pathways. Glutathione metabolism was enriched through glutamic acid and pyroglutamic acid, indicating potential modulation of redox homeostasis and antioxidant defenses. Pyrimidine metabolism involved cytidine monophosphate, uridine 5′-monophosphate, and uracil, suggesting possible shifts in nucleotide biosynthesis and degradation. Plasmalogen synthesis was associated with cytidine monophosphate and stearic acid, pointing to potential alterations in membrane lipid remodeling.

Fig. 4.

Fig. 4

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Metabolic pathway enrichment analysis of significantly altered metabolites between Syrian refugee and Jordanian women. Bar lengths represent the enrichment ratio, while colors correspond to the statistical significance (p-value), with red indicating more significant enrichment and yellow indicating less significant enrichment.

4. Discussion

Here, we observed that education level, employment status and other wellness indicators were significantly lower among Syrian refugee women than Jordanian women (control group). Importantly, the Syrian refugee group exhibited significant perceived stress when compared to control group. This is not surprising considering the negative consequences of trauma, conflict, war, displacement and resettlement (Atrooz et al., 2022). Clearly, refugees are at heightened risk of chronic stress due to experiences of conflict, displacement, resettlement, poverty, and social isolation, and access to health care is often limited, due to financial difficulties, and legal restrictions. Importantly, stigma compounds these issues, as mental illness is associated with shame, weakness, or social exclusion, leading individuals to hide their symptoms or avoid seeking care. Together, these barriers contribute to untreated chronic stress and worse health outcomes. Addressing these challenges requires stigma-reducing approaches, such as a biomarker-based mental health screening system.

Our untargeted metabolomic analysis revealed coordinated disturbances across four interlinked pathways, purine metabolism, glutathione metabolism, pyrimidine metabolism, and plasmalogen synthesis, suggesting a systemic metabolic reconfiguration centered around oxidative stress, nucleotide turnover, and membrane lipid vulnerability. The metabolic pathways identified in the present study are consistent with a growing body of metabolomic research examining psychological stress, trauma, and related psychiatric conditions. Alterations in purine metabolism, including elevations in hypoxanthine and nucleotide metabolites, have been reported in both human and experimental studies of chronic stress and depression (Hamilton et al., 2020). Similarly, disruptions in glutathione-dependent antioxidant pathways and oxidative stress markers are among the most consistently observed biochemical features of stress-related psychopathology (Mellon et al., 2018). Recent metabolomic investigations have also implicated oxidative stress, lipid remodeling, and inflammatory processes as key biological correlates of chronic stress (Frontiers in Psychiatry, 2023; Molecular Psychiatry, 2022). Collectively, these findings support the biological plausibility of the pathway alterations observed in the current study and suggest that disturbances in redox homeostasis and nucleotide metabolism may represent conserved metabolic signatures of chronic stress exposure across diverse populations. The alterations in purine metabolism, reflected by elevations in guanine, hypoxanthine, glutamic acid, and deoxyadenosine monophosphate (dAMP), underscore accelerated nucleotide turnover and dysfunction in salvage pathways. Elevated hypoxanthine is particularly noteworthy as a substrate of xanthine oxidase, an enzymatic process that generates reactive oxygen species (ROS) (Aziz and Jamil, 2023; Furuhashi and Metabolism, 2020). The concomitant increase in guanine and dAMP suggests heightened purine catabolism alongside impaired nucleotide recycling, potentially reflecting stress-induced DNA damage and repair activity (Ventura et al., 2010). The rise in glutamic acid, a central precursor in both purine biosynthesis and glutathione metabolism, further indicates redox imbalance and increased cellular demand for antioxidant defense (Amores-Sánchez et al., 1999). Comparable disturbances in purine metabolism have been reported in major depressive disorder, where enhanced nucleotide degradation and altered uric acid dynamics are closely associated with symptom severity and oxidative stress (Hamilton et al., 2020). Consistent with this, glutathione metabolism emerged as a compensatory response, reflected by significant increases in both glutamic acid and pyroglutamic acid. Pyroglutamic acid, an intermediate in the γ-glutamyl cycle, is considered a sensitive indicator of glutathione turnover and oxidative stress load, and a marker of systemic oxidative burden in patients (Gamarra et al., 2019). Also, psychiatric metabolomics consistently demonstrate that depressed individuals exhibit impaired glutathione metabolism, with reduced antioxidant defenses and altered redox homeostasis (Qianhao et al.). Our data thus suggest that increased glutathione cycling may represent an adaptive but potentially insufficient countermeasure to oxidative stress.

Moreover, alterations in pyrimidine metabolism, including elevations in CMP, UMP, and uracil, implicate stress-induced remodeling of nucleotide biosynthesis and RNA turnover. Pyrimidine dysregulation may reflect increased transcriptional demand and concurrent RNA catabolism, processes sensitive to oxidative stress. Pyrimidines also play neuroprotective roles by facilitating phospholipid biosynthesis and promoting synaptic plasticity. Uridine contributes to neuronal membrane assembly and enhances the expression of synaptic proteins, supports dendritic spine outgrowth and synaptic formation, thereby bolstering adaptive neuroplastic responses. These mechanisms are particularly relevant during acute stress, when synaptic turnover and membrane repair are elevated under chronic stress, these compensatory processes may become inadequate, resulting in synaptic and cognitive compromise. Such neurochemical dynamics are supported by evidence that uridine supplementation improves synapse formation and cognitive outcomes in experimental models (Wurtman et al., 2009).

In parallel with these biochemical shifts, disturbances in membrane lipid metabolism provide further support oxidative vulnerability. Plasmalogens are peroxisome-derived ether glycerophospholipids, with ethanolamine plasmalogens being the most abundant in the brain. Within neuronal membranes, plasmalogens modulate bilayer packing, curvature, lateral pressure, and lipid–raft organization (Dean et al., 2018; Dorninger et al., 2022). Functionally, the vinyl-ether bond at the sn-1 position is highly reactive toward oxidants, enabling plasmalogens to act as sacrificial antioxidants that protect neighboring polyunsaturated lipids and membrane proteins from oxidative injury (Brosche and Platt, 1998). In the present study, the observed increase in cytidine monophosphate (CMP) alongside a reduction in stearic acid is coherent with active phospholipid remodeling. CMP is a stoichiometric by-product of phosphatidyltransferase reactions in the Kennedy pathway, which utilize CDP-activated intermediates (e.g., CDP-choline or CDP-ethanolamine) to generate membrane phospholipids, including ether lipids. Meanwhile, depletion of saturated acyl chains such as stearic acid is consistent with oxidative membrane turnover and reacylation processes (Lands cycle) occurring under elevated redox pressure (Dean et al., 2018). These findings support the interpretation that oxidative lipid remodeling is underway in chronically stressed individuals, wherein plasmalogens are consumed as frontline antioxidants while membrane composition is actively rebalanced to maintain structural integrity (Almsherqi and Biology, 2021; Su et al., 2019). Importantly, both experimental and clinical evidence indicates that restoration or preservation of plasmalogen pools mitigates oxidative injury and supports synaptic function, underscoring the translational significance of ether lipid pathways in stress-related conditions (Goodenowe et al., 2022).

Together, these findings indicate that chronic stress is not defined by isolated metabolic changes but by a coordinated cascade driven by oxidative stress. Purine catabolism increases ROS production, which in turn triggers compensatory glutathione turnover. At the same time, pyrimidine flux rises to sustain transcriptional and repair demands, while plasmalogen loss weakens membrane resilience. This interconnected pattern indicates oxidative stress as the central hub linking nucleotide imbalance, inadequate antioxidant defenses, and lipid remodeling. Importantly, this cascade mirrors metabolic disturbances consistently observed in depression, PTSD, and anxiety (Hamilton et al., 2020; Qianhao et al., 2025). Moreover, specific metabolites, such as hypoxanthine, glutamic acid, cytidine monophosphate, and plasmalogens, emerge as promising salivary biomarkers for non-invasive assessment of chronic stress.

4.1. Limitations

This study has several limitations that should be considered when interpreting the findings. First, the cross-sectional design precludes any conclusions regarding causality or temporal relationships between perceived stress and metabolomic alterations. The observed associations should therefore be interpreted as correlational rather than causal. Second, the study compared Syrian refugee women with Jordanian women, and although perceived stress levels differed between groups, metabolomic differences may also reflect unmeasured factors including socioeconomic conditions, dietary habits, healthcare access, environmental exposures, cultural influences, and migration-related experiences. Significant differences in education, income, employment, and health insurance status between groups may have contributed to the observed metabolic profiles. Third, several potentially important variables known to influence salivary metabolomics were not systematically assessed, including dietary intake, nutritional supplementation, medication use, oral health status, physical activity, menopausal status, recent infections, and sleep quality. In addition, information regarding duration of residence in Jordan, age at migration, displacement history, and refugee camp versus urban residence was not collected, limiting our ability to evaluate the influence of migration-related exposures on metabolomic outcomes. These factors may represent sources of residual confounding. Fourth, saliva reflects both host and oral microbial metabolism. Consequently, some of the identified metabolites and enriched pathways may be influenced by variations in oral microbiome composition rather than host metabolic processes alone. Because oral microbiome profiling was not performed, the relative contribution of microbial versus host-derived metabolites could not be determined. Fifth, although high-resolution UHPLC-QTOF mass spectrometry was employed, metabolite identification was based primarily on accurate mass, isotope patterns, and MS/MS spectral matching without confirmation using authentic reference standards for all metabolites. Therefore, metabolite annotations correspond largely to putatively identified compounds (MSI Level 2), and misannotation remains possible. Furthermore, pathway enrichment analyses depend on available database annotations and may not capture all biologically relevant pathways represented in the metabolomic dataset. Finally, since 75% of the samples were unusable for downstream metabolomics, this remains a substantive limitation, therefore we have refrained from generalizing the metabolomic differences from the 25-sample subset. Although exploratory analyses identified biologically plausible pathways associated with perceived stress, replication in larger, longitudinal, and more diverse refugee populations is needed to confirm these findings and evaluate the utility of salivary metabolomic markers as indicators of stress-related mental health outcomes. Despite these limitations, this study is among the first to integrate psychosocial assessments with untargeted salivary metabolomics in Syrian refugee women. The use of a noninvasive biospecimen, combined with validated psychological measures, provides novel insights into the biological correlates of perceived stress in a highly understudied and vulnerable population and establishes a foundation for future longitudinal biomarker research.

Statements and declarations

Funding

This work was supported by US Depart of State, RAWABIT and Jordan Fulbright. 2023 Friends of Women’s Gender Sexuality Studies (WGSS) Faculty Summer Fellowship, University of Houston WGSS program awarded to Dr. Samina Salim. Also, This study was financially supported by the University of Sharjah, UAE. Funding was provided by the Research Funding Department under grant numbers 2301,110,278 and 2301,110,381 (K.H.A.), and 24,011,101,105 (M.H.S.).

Protection of human subjects

The study was approved by the Institutional Review Board (IRB) Committee for the Protection of Human Subjects, University of Houston (UH), Houston, TX, USA (STUDY00002929) and by the Jordan University of Science and Technology (JUST) IRB, Irbid, Jordan (IRB#52/148/2022, 10.05.2022).

CRediT authorship contribution statement

Fatin Atrooz: Writing – review & editing, Writing – original draft, Visualization, Validation, Methodology, Investigation, Formal analysis, Data curation. Ruba A. Zenati: Writing – review & editing, Writing – original draft, Methodology, Formal analysis, Data curation. Mohammad H. Semreen: Writing – review & editing, Writing – original draft, Validation, Supervision, Software, Resources, Methodology, Investigation, Formal analysis, Data curation. Karem H. Alzoubi: Writing – review & editing, Writing – original draft, Supervision, Resources, Project administration, Methodology, Investigation, Funding acquisition. Hamza M. Al-Hroub: Writing – review & editing, Writing – original draft, Validation, Methodology, Formal analysis, Data curation. Yasser Bustanji: Writing – review & editing, Methodology, Formal analysis. Omar F Khabour: Writing – review & editing, Writing – original draft, Project administration, Data curation, Conceptualization. Sally Aljararwah: Writing – review & editing, Methodology, Formal analysis, Data curation. Samina Salim: Writing – review & editing, Writing – original draft, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization.

Declaration of competing interest

“The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.”

Acknowledgements

The authors gratefully acknowledge the help of JUST colleagues for their help in the study.

Contributor Information

Mohammad H. Semreen, Email: msemreen@sharjah.ac.ae.

Samina Salim, Email: ssalim@uh.edu.

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