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A pilot study reveals plasma metabolomic and lipidomic signatures of mustard lung disease
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  • Published: 20 February 2026

A pilot study reveals plasma metabolomic and lipidomic signatures of mustard lung disease

  • B. Fatemeh Nobakht M. Gh.1,
  • Hasan Bagheri1,
  • Uri Keshet2 &
  • …
  • Mostafa Ghanei1 

Scientific Reports , Article number:  (2026) Cite this article

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Biochemistry
  • Biological techniques
  • Biomarkers
  • Diseases

Abstract

Accurately diagnosing mustard lung disease (MLD) presents a significant challenge due to its intricate nature and overlapping clinical features with other pulmonary conditions. A precise diagnosis is crucial for effective therapeutic management and optimizing patient care. Furthermore, understanding the metabolic shifts induced by sulfur mustard (SM) exposure is critical for elucidating the disease’s mechanisms and developing targeted interventions. This study employed an untargeted metabolomics and lipidomics profiling by liquid chromatography-mass spectrometry (LC-MS). We analyzed samples from MLD patients (n = 39; 20 mild, 19 moderate severity) and a control group (n = 14). We used multivariate/univariate statistical methods to identify distinguishing metabolites and lipids, and then performed pathway enrichment analysis to uncover the perturbed biochemical pathways. Our results demonstrated significant metabolic disruptions in MLD patients. We identified 16 metabolite panels capable of diagnosing mild MLD against controls, and 22 metabolite panels for moderate MLD versus controls (AUC > 0.85). Additionally, in comparison with the control group, four lipids were detected in the mild MLD group and five in the moderate MLD group (p-value < 0.05). Our findings reveal unique metabolite and lipid profiles and widespread disturbances across various metabolic pathways, including amino acid, butyrate, propanoate metabolism, and carnitine synthesis, which differentiate MLD from controls. This research represents the first investigation into metabolomic and lipidomic signatures that discriminate MLD from control groups using LC-MS. Significant metabolites show promise as candidate biomarkers for MLD diagnosis or prognosis and offer valuable insights for further research into the disease’s pathological mechanisms, pending validation in larger prospective cohorts.

Data availability

The raw data that support the findings of this study are available on permission request from the Director of Chemical Injuries Research Center, Hasan Bagheri as third party. The data are not publicly available due to restrictions e.g. their containing information that could compromise the privacy of research participants and third-party laws.

Abbreviations

SM:

Sulfur mustard

MLD:

Mustard lung disease

COPD:

Chronic obstructive pulmonary disease

NMR:

Nuclear magnetic resonance

LC:

Liquid chromatography

GC:

Gas chromatography

MS:

Mass spectrometry

HRCT:

High-resolution computed tomography

PFT:

Pulmonary function tests

HILIC:

Hydrophilic interaction liquid chromatography

ACN:

Acetonitrile

AF:

Ammonium formate

FA:

Formic acid

QC:

Quality control

CV:

Coefficient of variability

MSI:

Metabolomics standards initiative

PCA:

Principal component analysis

OPLS-DA:

Orthogonal projections to latent structures-discriminant analysis

ROC:

Receiver-operating characteristic

AUC:

Area under the ROC curve

VIP:

Variable importance in projection

MSEA:

Metabolite set enrichment analysis

MDD:

Major depressive disorder

VLCFA:

Very long-chain fatty acid

EPA:

Eicosapentaenoic acid

ARDS:

Acute respiratory distress syndrome

ADMA:

Asymmetric dimethylarginine

ROS:

Reactive oxygen species

TCA:

Citric acid cycle

HIF-1α:

Hypoxia-inducible factor 1-alpha

NAC:

N-acetylcysteine

PGE-1:

Prostaglandin E1

References

  1. Balali-Mood, M. & Hefazi, M. Comparison of early and late toxic effects of sulfur mustard in Iranian veterans. Basic Clin. Pharmacol. Toxicol. 99 (4), 273–282 (2006).

    Google Scholar 

  2. Darchini-Maragheh, E. & Balali-Mood, M. Delayed complications and long-term management of sulfur mustard poisoning: recent advances by Iranian researchers (part I of II). Iran. J. Med. Sci. 43 (2), 103 (2018).

    Google Scholar 

  3. Moradi, F., Moradi, F., Li, Y., Olin, A-C. & Daka, B. The impact of sulfur mustard on quality of life and mental health in Kurdish survivors in Sweden, Thirty years after exposure. Health Qual. Life Outcomes. 20 (1), 165 (2022).

    Google Scholar 

  4. Amini, H. et al. Long-term health outcomes among survivors exposed to sulfur mustard in Iran. JAMA Netw. open. 3 (12), e2028894 (2020).

    Google Scholar 

  5. Weinberger, B. et al. Sulfur mustard-induced pulmonary injury: therapeutic approaches to mitigating toxicity. Pulm. Pharmacol. Ther. 24 (1), 92–99 (2011).

    Google Scholar 

  6. Kehe, K. & Szinicz, L. Medical aspects of sulphur mustard poisoning. Toxicology 214 (3), 198–209 (2005).

    Google Scholar 

  7. Kehe, K. et al. Sulfur mustard research—strategies for the development of improved medical therapy. Eplasty 8, e32 (2008).

    Google Scholar 

  8. Abtahi, H., Peiman, S., Foroumandi, M. & Safavi, E. Long term follow-up of sulfur mustard related bronchiolitis obliterans treatment. Acta Med. Iranica 605–609 (2016).

  9. Shahriary, A., Ghanei, M. & Rahmani, H. The systemic nature of mustard lung: comparison with COPD patients. Interdiscipl. Toxicol. 10 (3), 114 (2017).

    Google Scholar 

  10. Saber, H., Saburi, A. & Ghanei, M. Clinical and paraclinical guidelines for management of sulfur mustard induced bronchiolitis obliterans; from bench to bedside. Inhalation Toxicol. 24 (13), 900–906 (2012).

    Google Scholar 

  11. Bagheri, M., Hosseini, S., Mostafavi, S. & Alavi, S. High-resolution CT in chronic pulmonary changes after mustard gas exposure. Acta Radiol. 44 (3), 241–245 (2003).

    Google Scholar 

  12. Ghanei, M., Mokhtari, M., Mohammad, M. M. & Aslani, J. Bronchiolitis obliterans following exposure to sulfur mustard: chest high resolution computed tomography. Eur. J. Radiol. 52 (2), 164–169 (2004).

    Google Scholar 

  13. Ghanei, M. et al. An international collaborative pathologic study of surgical lung biopsies from mustard gas-exposed patients. Respir. Med. 102 (6), 825–830 (2008).

    Google Scholar 

  14. Freitag, L., Firusian, N., Stamatis, G. & Greschuchna, D. The role of bronchoscopy in pulmonary complications due to mustard gas inhalation. Chest 100 (5), 1436–1441 (1991).

    Google Scholar 

  15. Jamshidi, V. et al. Plasma and urine metabolomics for the identification of diagnostic biomarkers for sulfur mustard-induced lung injury. Int. Immunopharmacol. 154, 114515 (2025).

    Google Scholar 

  16. Nobakht, B. F. et al. NMR-and GC/MS-based metabolomics of sulfur mustard exposed individuals: a pilot study. Biomarkers 21 (6), 479–489 (2016).

    Google Scholar 

  17. Nobakht, B. F. et al. NMR spectroscopy-based metabolomic study of serum in sulfur mustard exposed patients with lung disease. Biomarkers 22 (5), 413–419 (2017).

    Google Scholar 

  18. Ghoochani, B. F. N. M. et al. Metabolomics diagnostic approach to mustard airway diseases: a preliminary study. Iran. J. Basic. Med. Sci. 21 (1), 59 (2018).

    Google Scholar 

  19. Nambiar, S., Bong How, S., Gummer, J., Trengove, R. & Moodley, Y. Metabolomics in chronic lung diseases. Respirology 25 (2), 139–148 (2020).

    Google Scholar 

  20. Newgard, C. B. Metabolomics and metabolic diseases: where do we stand? Cell Metabol. 25 (1), 43–56 (2017).

    Google Scholar 

  21. Ran, N. et al. An updated overview of metabolomic profile changes in chronic obstructive pulmonary disease. Metabolites 9 (6), 111 (2019).

    Google Scholar 

  22. Chetwynd, A. J., Dunn, W. B. & Rodriguez-Blanco, G. Collection and Preparation of clinical samples for metabolomics. Metab. Fundam. Clin. Appl. 19–44 (2017).

  23. Ovbude, S. T. et al. Applications of chromatographic methods in metabolomics: A review. J. Chromatogr. B 124124 (2024).

  24. McCullagh, J. & Probert, F. New analytical methods focusing on polar metabolite analysis in mass spectrometry and NMR-based metabolomics. Curr. Opin. Chem. Biol. 80, 102466 (2024).

    Google Scholar 

  25. Ismail, I. T. et al. Remodeling lipids in the transition from chronic liver disease to hepatocellular carcinoma. Cancers 13 (1), 88 (2020).

    Google Scholar 

  26. Dahabiyeh, L. A., Nimer, R. M., Wells, J. D., Abu-Rish, E. Y. & Fiehn, O. Diagnosing parkinson’s disease and monitoring its progression: biomarkers from combined GC-TOF MS and LC-MS/MS untargeted metabolomics. Heliyon 10(9). (2024).

  27. Mahadevan, S., Shah, S. L., Marrie, T. J. & Slupsky, C. M. Analysis of metabolomic data using support vector machines. Anal. Chem. 80 (19), 7562–7570 (2008).

    Google Scholar 

  28. Liu, J. et al. Integrated metabolome and microbiome analysis reveals the effect of rumen-protected sulfur-containing amino acids on the meat quality of Tibetan sheep meat. Front. Microbiol. 15, 1345388 (2024).

    Google Scholar 

  29. Jiang, N., Zhang, P., Shen, W., Zhang, Y. & Zhou, W. Clinical and experimental research progress on neurotoxicity of sulfur mustard and its possible mechanisms. Toxicology 483, 153372 (2023).

    Google Scholar 

  30. Kageyama, Y. et al. Plasma nervonic acid is a potential biomarker for major depressive disorder: a pilot study. Int. J. Neuropsychopharmacol. 21 (3), 207–215 (2018).

    Google Scholar 

  31. Stradomska, T. J. et al. Serum very long-chain fatty acids (VLCFA) levels as predictive biomarkers of diseases severity and probability of survival in peroxisomal disorders. PLoS One. 15 (9), e0238796 (2020).

    Google Scholar 

  32. Rutkowsky, J. M. et al. Acylcarnitines activate Proinflammatory signaling pathways. Am. J. Physiol.-Endocrinol. Metab. 306 (12), E1378–E87 (2014).

    Google Scholar 

  33. Ghaffarpour, S. et al. Evaluation of TLR4 gene expression in mustard gas injured persons’ lungs. Iran. J. War Public. Health. 6 (4), 171–176 (2014).

    Google Scholar 

  34. Sidletskaya, K., Vitkina, T. & Denisenko, Y. The role of toll-like receptors 2 and 4 in the pathogenesis of chronic obstructive pulmonary disease. Int. J. Chronic Obstr. Pulm. Dis. 1481–1493 (2020).

  35. Garcia de Acilu, M. et al. The role of Omega-3 polyunsaturated fatty acids in the treatment of patients with acute respiratory distress syndrome: A clinical review. Biomed. Res. Int. 2015 (1), 653750 (2015).

    Google Scholar 

  36. de Batlle, J. et al. Association between Ω3 and Ω6 fatty acid intakes and serum inflammatory markers in COPD. J. Nutr. Biochem. 23 (7), 817–821 (2012).

    Google Scholar 

  37. Abdullah, L. et al. Translational potential of long-term decreases in mitochondrial lipids in a mouse model of Gulf war illness. Toxicology 372, 22–33 (2016).

    Google Scholar 

  38. Telenga, E. D. et al. Untargeted lipidomic analysis in chronic obstructive pulmonary disease. Uncovering sphingolipids. Am. J. Respir. Crit Care Med. 190 (2), 155–164 (2014).

    Google Scholar 

  39. Liu, D. et al. Identification of lipid biomarker from serum in patients with chronic obstructive pulmonary disease. Respir. Res. 21 (1), 242 (2020).

    Google Scholar 

  40. Zhou, J., Li, Q., Liu, C., Pang, R. & Yin, Y. Plasma metabolomics and lipidomics reveal perturbed metabolites in different disease stages of chronic obstructive pulmonary disease. Int. J. Chronic Obstr. Pulm. Dis. 553–565. (2020).

  41. Zinellu, A. et al. Systemic concentrations of asymmetric dimethylarginine (ADMA) in chronic obstructive pulmonary disease (COPD): state of the Art. Amino Acids. 50, 1169–1176 (2018).

    Google Scholar 

  42. Du, M-R., Ju, G-X., Li, N-S. & Jiang, J-L. Role of asymmetrical dimethylarginine in diabetic microvascular complications. J. Cardiovasc. Pharmacol. 68 (4), 322–326 (2016).

    Google Scholar 

  43. Roshan Lal, T., Cechinel, L. R., Freishtat, R. & Rastogi, D. Metabolic contributions to pathobiology of asthma. Metabolites 13 (2), 212 (2023).

    Google Scholar 

  44. Bouras, G. et al. Asymmetric dimethylarginine (ADMA): a promising biomarker for cardiovascular disease? Curr. Top. Med. Chem. 13 (2), 180–200 (2013).

    Google Scholar 

  45. Darvishi, B., Panahi, Y., Ghanei, M. & Farahmand, L. Investigating prevalence and pattern of Long-term cardiovascular disorders in sulphur Mustard‐exposed victims and determining proper biomarkers for early Defining, monitoring and analysis of patients’ feedback on therapy. Basic Clin. Pharmacol. Toxicol. 120 (2), 120–130 (2017).

    Google Scholar 

  46. Becerra-Diaz, M., Song, M. & Heller, N. Androgen and androgen receptors as regulators of monocyte and macrophage biology in the healthy and diseased lung. Front. Immunol. 11, 1698 (2020).

    Google Scholar 

  47. Montaño, L. M., Flores-Soto, E., Sommer, B., Solís-Chagoyán, H. & Perusquía, M. Androgens are effective bronchodilators with anti-inflammatory properties: A potential alternative for asthma therapy. Steroids 153, 108509 (2020).

    Google Scholar 

  48. Han, Y-Y. et al. Serum free testosterone and asthma, asthma hospitalisations and lung function in British adults. Thorax 75 (10), 849–854 (2020).

    Google Scholar 

  49. Shahin, S., Cullinane, C. & Gray, P. J. Mitochondrial and nuclear DNA damage induced by sulphur mustard in keratinocytes. Chemico-Biol. Interact. 138 (3), 231–245 (2001).

    Google Scholar 

  50. Gould, N. S., White, C. W. & Day, B. J. A role for mitochondrial oxidative stress in sulfur mustard analog 2-chloroethyl Ethyl sulfide-induced lung cell injury and antioxidant protection. J. Pharmacol. Exp. Ther. 328 (3), 732–739 (2009).

    Google Scholar 

  51. Yan, Y. et al. Adenosine monophosphate activated protein kinase contributes to skeletal muscle health through the control of mitochondrial function. Front. Pharmacol. 13, 947387 (2022).

    Google Scholar 

  52. Antunes, M. A., Lopes-Pacheco, M. & Rocco, P. R. Oxidative stress-derived mitochondrial dysfunction in chronic obstructive pulmonary disease: A concise review. Oxidative Med. Cell. Longev. 2021 (1), 6644002 (2021).

    Google Scholar 

  53. Mateska, I. et al. Succinate mediates inflammation-induced adrenocortical dysfunction. Elife 12, e83064 (2023).

    Google Scholar 

  54. Zhang, Y. et al. Succinate accumulation induces mitochondrial reactive oxygen species generation and promotes status epilepticus in the Kainic acid rat model. Redox Biol. 28, 101365 (2020).

    Google Scholar 

  55. Tannahill, G. et al. Succinate is an inflammatory signal that induces IL-1β through HIF-1α. Nature 496 (7444), 238–242 (2013).

    Google Scholar 

  56. Wang, Y-H. et al. Gut microbiota-derived succinate aggravates acute lung injury after intestinal ischaemia/reperfusion in mice. Eur. Respir. J. 61(2). (2023).

  57. Shohrati, M., Karimzadeh, I., Saburi, A., Khalili, H. & Ghanei, M. The role of N-acetylcysteine in the management of acute and chronic pulmonary complications of sulfur mustard: a literature review. Inhalation Toxicol. 26 (9), 507–523 (2014).

    Google Scholar 

  58. Pohanka, M., Sobotka, J., Jilkova, M. & Stetina, R. Oxidative stress after sulfur mustard intoxication and its reduction by melatonin: efficacy of antioxidant therapy during serious intoxication. Drug Chem. Toxicol. 34 (1), 85–91 (2011).

    Google Scholar 

  59. Tong, W-H. & Rouault, T. A. Metabolic regulation of citrate and iron by aconitases: role of iron–sulfur cluster biogenesis. Biometals 20, 549–564 (2007).

    Google Scholar 

  60. Tejwani, V. et al. Airway and systemic prostaglandin E2 association with COPD symptoms and macrophage phenotype. Chronic Obstr. Pulm. Dis. J. COPD Found. 10 (2), 159 (2023).

    Google Scholar 

  61. Dujisc, Ž., Eterovic, D., Tocilj, J., Kusid, Z. & Čapkun, V. About mechanisms of prostaglandin E1 induced deterioration of pulmonary gas exchange in COPD patients. Clin. Physiol. 13 (5), 497–506 (1993).

    Google Scholar 

  62. Gonçalves-de-Albuquerque, C. F., Silva, A. R., Burth, P., Castro-Faria, M. V. & Castro-Faria-Neto, H. C. Acute respiratory distress syndrome: role of oleic acid-triggered lung injury and inflammation. Mediat. Inflamm. 2015 (1), 260465 (2015).

    Google Scholar 

  63. Gonçalves-de-Albuquerque, C. F., Silva, A. R., Burth, P., Castro-Faria, M. V. & Castro-Faria-Neto, H. C. Oleic Acid and Lung Injury. Handbook of Lipids in Human Function, 605–634 (Elsevier, 2016).

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Acknowledgements

The authors extend their gratitude to the study participants for their invaluable contributions to scientific advancement. Additionally, sincere appreciation is expressed to the Cohort Study of Iranian Chemical Injured (CICI Study) at Baqiyatallah University of Medical Sciences (Ethical approval: IR.BMSU.REC.1399.422) for their essential support in facilitating sample collection, preparation, and biobanking.

Funding

This work was supported financially by the grant which has been taken from Baqiyatallah University of Medical Sciences.

Author information

Authors and Affiliations

  1. Chemical Injuries Research Center, Systems Biology and Poisoning Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran

    B. Fatemeh Nobakht M. Gh., Hasan Bagheri & Mostafa Ghanei

  2. West Coast Metabolomics Center, University of California, Davis, CA, USA

    Uri Keshet

Authors
  1. B. Fatemeh Nobakht M. Gh.
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  2. Hasan Bagheri
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  3. Uri Keshet
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  4. Mostafa Ghanei
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Contributions

H.B.: Conceptualization, project administration, funding acquisition, writing—review and editing. U.K.: Methodology, formal analysis, visualization, writing—review and editing. M.G.: Conceptualization, supervision, project administration, writing—review and editing. B.F.N.M.Gh: Investigation, software, methodology, formal analysis, validation, writing—original draft, writing—review and editing.

Corresponding author

Correspondence to B. Fatemeh Nobakht M. Gh..

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In preparing this publication, the authors utilized Gemini for paraphrasing some sections of the article. Following the use of this tool, the content was thoroughly reviewed and edited by the authors, who assume full responsibility for the final published article.

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Nobakht M. Gh., B.F., Bagheri, H., Keshet, U. et al. A pilot study reveals plasma metabolomic and lipidomic signatures of mustard lung disease. Sci Rep (2026). https://doi.org/10.1038/s41598-026-39675-1

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  • Received: 21 October 2025

  • Accepted: 06 February 2026

  • Published: 20 February 2026

  • DOI: https://doi.org/10.1038/s41598-026-39675-1

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Keywords

  • Plasma
  • Mustard lung disease
  • Metabolomics
  • Lipidomics
  • Mass spectrometry
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