Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Advertisement

Scientific Reports
  • View all journals
  • Search
  • My Account Login
  • Content Explore content
  • About the journal
  • Publish with us
  • Sign up for alerts
  • RSS feed
  1. nature
  2. scientific reports
  3. articles
  4. article
Prevalence of low bone mineral density and associated plasma metabolite alterations in thalassemia
Download PDF
Download PDF
  • Article
  • Open access
  • Published: 03 January 2026

Prevalence of low bone mineral density and associated plasma metabolite alterations in thalassemia

  • Pokpong Piriyakhuntorn1,
  • Adisak Tantiworawit1,
  • Piangrawee Niprapan1,
  • Chanisa Thonusin2,3,4,
  • Wichwara Nawara3,4,
  • Tawika Kaewchur5,
  • Nipon Chattipakorn2,3,4,6 &
  • …
  • Siriporn C. Chattipakorn3,4,7 

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

  • 926 Accesses

  • 1 Altmetric

  • Metrics details

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
  • Biomarkers
  • Diseases
  • Endocrinology
  • Medical research

Abstract

While metabolomics offers insights into metabolic diseases, plasma metabolites in thalassemia patients with low bone mineral density (BMD) have not been explored. This cross-sectional study investigated plasma metabolite alterations in thalassemia patients with low BMD compared to those with normal BMD and healthy controls at Chiang Mai University’s Hematology Clinic. Eighty thalassemia patients and 40 age- and sex-matched controls were enrolled. BMD was measured at two skeletal sites, the lumbar spine (L1–L4) and hip, using dual-energy X-ray absorptiometry. Targeted plasma metabolomics and bone turnover markers (β-CTX-I, total PINP) were assessed. Low BMD was defined as a Z-score ≤ − 2 at any site, and its prevalence among thalassemia patients was 47.5%. Compared to those with normal BMD, thalassemia patients with low BMD showed elevated glutamate, arachidonic acid, and medium- to long-chain acylcarnitines, but reduced glutamine levels. Phosphatidylinositol and lysophosphatidylinositol were also increased. β-CTX-I and total PINP levels did not differ between thalassemia groups. A predictive model using key metabolites (glutamine, arachidonic acid, asparagine, lysoPI (18:0), myristoylcarnitine) showed fair discriminatory ability for low BMD (AUC 0.762, p = 0.007). Thalassemia with low BMD is associated with glutamate–glutamine metabolism disruptions, impaired fatty acid oxidation, and elevated phosphatidylinositol levels.

Similar content being viewed by others

Association between testosterone levels and bone mineral density in females aged 40–60 years from NHANES 2011–2016

Article Open access 30 September 2022

Changes in bone turnover markers and bone modulators during abatacept treatment

Article Open access 11 October 2023

Association between triglycerides and lumbar bone mineral density in Chinese patients with osteoporotic fractures: a retrospective cross-sectional study

Article Open access 27 November 2024

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request. Some data may not be made available due to privacy or ethical restrictions.

References

  1. Cappellini, M-D., Cohen, A., Porter, J., Taher, A. & Viprakasit, V. Guidelines for the management of transfusion dependent thalassaemia (TDT). Nicosia (CY): Thalassaemia International Federation (2014). https://www.ncbi.nlm.nih.gov/books/NBK269382/?report=classic

  2. Consensus development conference: diagnosis, prophylaxis, and treatment of osteoporosis. Am. J. Med. 94(6), 646–650 (1993).

  3. Gordon, C. M. et al. Dual energy X-ray absorptiometry interpretation and reporting in children and adolescents: the 2007 ISCD pediatric official positions. J. Clin. Densitom. 11 (1), 43–58 (2008).

    Google Scholar 

  4. Sutipornpalangkul, W., Janechetsadatham, Y., Siritanaratkul, N. & Harnroongroj, T. Prevalence of fractures among Thais with thalassaemia syndromes. Singap. Med. J. 51 (10), 817–821 (2010).

    Google Scholar 

  5. Zhang, X., Li, Q., Xu, Z. & Dou, J. Mass spectrometry-based metabolomics in health and medical science: a systematic review. RSC Adv. 10 (6), 3092–3104 (2020).

    Google Scholar 

  6. Zhao, Q. et al. Metabolomic profiles associated with bone mineral density in US Caucasian women. Nutr. Metab. (Lond). 15, 57 (2018).

    Google Scholar 

  7. Miyamoto, T. et al. A serum metabolomics-based profile in low bone mineral density postmenopausal women. Bone 95, 1–4 (2017).

    Google Scholar 

  8. Wang, J. et al. Discovery of potential biomarkers for osteoporosis using LC-MS/MS metabolomic methods. Osteoporos. Int. 30 (7), 1491–1499 (2019).

    Google Scholar 

  9. Musharraf, S. G. et al. beta-Thalassemia patients revealed a significant change of untargeted metabolites in comparison to healthy individuals. Sci. Rep. 7, 42249 (2017).

    Google Scholar 

  10. Wong, P., Fuller, P. J., Gillespie, M. T. & Milat, F. Bone disease in thalassemia: A molecular and clinical overview. Endocr. Rev. 37 (4), 320–346 (2016).

    Google Scholar 

  11. Lewiecki, E. M. et al. International society for clinical densitometry 2007 adult and pediatric official positions. Bone 43 (6), 1115–1121 (2008).

    Google Scholar 

  12. Thonusin, C. et al. Blood metabolomes as non-invasive biomarkers and targets of metabolic interventions for doxorubicin and trastuzumab-induced cardiotoxicity. Arch. Toxicol. 97 (2), 603–618 (2023).

    Google Scholar 

  13. Thonusin, C. et al. Evaluation of intensity drift correction strategies using MetaboDrift, a normalization tool for multi-batch metabolomics data. J. Chromatogr. A. 1523, 265–274 (2017).

    Google Scholar 

  14. Mahachoklertwattana, P. et al. Bone mineral density, biochemical and hormonal profiles in suboptimally treated children and adolescents with beta-thalassaemia disease. Clin. Endocrinol. (Oxf). 58 (3), 273–279 (2003).

    Google Scholar 

  15. Cochran, W. G. Sampling Techniques, 3d edn., xvi (Wiley, 1977).

  16. Pang, Z. et al. MetaboAnalyst 6.0: towards a unified platform for metabolomics data processing, analysis and interpretation. Nucleic Acids Res. 52 (W1), W398–W406 (2024).

    Google Scholar 

  17. Chen, X. et al. Amniotic fluid metabolomic and lipidomic alterations associated with hemoglobin bart’s diseases. Metabolomics 17 (9), 82 (2021).

    Google Scholar 

  18. Monni, G. et al. Metabolomic investigation of beta-Thalassemia in chorionic villi samples. J. Clin. Med. ;8(6). (2019).

  19. Iqbal, A. et al. Hydroxyurea treated beta-Thalassemia children demonstrate a shift in metabolism towards healthy pattern. Sci. Rep. 8 (1), 15152 (2018).

    Google Scholar 

  20. Tzounakas, V. L. et al. Beta thalassemia minor is a beneficial determinant of red blood cell storage lesion. Haematologica 107 (1), 112–125 (2022).

    Google Scholar 

  21. Hortle, E. et al. Adenosine monophosphate deaminase 3 activation shortens erythrocyte half-life and provides malaria resistance in mice. Blood 128 (9), 1290–1301 (2016).

    Google Scholar 

  22. Rejnmark, L., Vestergaard, P., Brot, C. & Mosekilde, L. Parathyroid response to vitamin D insufficiency: relations to bone, body composition and to lifestyle characteristics. Clin. Endocrinol. (Oxf). 69 (1), 29–35 (2008).

    Google Scholar 

  23. Rodbro, L. L., Bislev, L. S., Sikjaer, T. & Rejnmark, L. Bone metabolism, density, and geometry in postmenopausal women with vitamin D insufficiency: a cross-sectional comparison of the effects of elevated parathyroid levels. Osteoporos. Int. 29 (10), 2211–2218 (2018).

    Google Scholar 

  24. Tsartsalis, A. N. et al. Bone metabolism markers in thalassemia major-induced osteoporosis: results from a cross-sectional observational study. Curr. Mol. Med. 19 (5), 335–341 (2019).

    Google Scholar 

  25. Celik, T., Sangun, O., Unal, S., Balci, A. & Motor, S. Assessment of biochemical bone markers of osteoporosis in children with thalassemia major. Ital. J. Pediatr. 48 (1), 105 (2022).

    Google Scholar 

  26. Das, L. et al. Bone turnover, areal BMD, and bone microarchitecture by second-generation high-resolution peripheral quantitative computed tomography in transfusion-dependent thalassemia. JBMR Plus. 8 (11), ziae117 (2024).

    Google Scholar 

  27. Baldini, M. et al. Thalassemic osteopathy: a new marker of bone deposition. Blood Cells Mol. Dis. 52 (2–3), 91–94 (2014).

    Google Scholar 

  28. Abdulrazzaq, Y. M., Ibrahim, A., Al-Khayat, A. I. & Dawson, K. Beta-thalassemia major and its effect on amino acid metabolism and growth in patients in the united Arab Emirates. Clin. Chim. Acta. 352 (1–2), 183–190 (2005).

    Google Scholar 

  29. Lyu, J. et al. A glutamine metabolic switch supports erythropoiesis. Science 386 (6723), eadh9215 (2024).

    Google Scholar 

  30. Kalpravidh, R. W. et al. Glutathione redox system in beta -thalassemia/Hb E patients. ScientificWorldJournal 2013, 543973 (2013).

    Google Scholar 

  31. Devignes, C. S., Carmeliet, G. & Stegen, S. Amino acid metabolism in skeletal cells. Bone Rep. 17, 101620 (2022).

    Google Scholar 

  32. Stegen, S. et al. Glutamine metabolism in osteoprogenitors is required for bone mass accrual and PTH-induced bone anabolism in male mice. J. Bone Min. Res. 36 (3), 604–616 (2021).

    Google Scholar 

  33. Yu, Y. et al. Glutamine metabolism regulates proliferation and lineage allocation in skeletal stem cells. Cell. Metab. 29 (4), 966–78e4 (2019).

    Google Scholar 

  34. Wauquier, F., Leotoing, L., Coxam, V., Guicheux, J. & Wittrant, Y. Oxidative stress in bone remodelling and disease. Trends Mol. Med. 15 (10), 468–477 (2009).

    Google Scholar 

  35. Domazetovic, V., Marcucci, G., Iantomasi, T., Brandi, M. L. & Vincenzini, M. T. Oxidative stress in bone remodeling: role of antioxidants. Clin. Cases Min. Bone Metab. 14 (2), 209–216 (2017).

    Google Scholar 

  36. Baek, K. H. et al. Association of oxidative stress with postmenopausal osteoporosis and the effects of hydrogen peroxide on osteoclast formation in human bone marrow cell cultures. Calcif Tissue Int. 87 (3), 226–235 (2010).

    Google Scholar 

  37. Dzubanova, M. et al. Glutamine: A novel player in maintaining skeletal strength and body fitness in obese mice. Clin. Nutr. 54, 162–176 (2025).

    Google Scholar 

  38. Bertolo, R. F. & Burrin, D. G. Comparative aspects of tissue glutamine and proline metabolism. J. Nutr. 138 (10), 2032S–9S (2008).

    Google Scholar 

  39. Gelse, K., Poschl, E. & Aigner, T. Collagens–structure, function, and biosynthesis. Adv. Drug Deliv. Rev. 55 (12), 1531–1546 (2003).

    Google Scholar 

  40. Bahar, A., Kashi, Z., Sohrab, M., Kosaryan, M. & Janbabai, G. Relationship between beta-globin gene carrier state and insulin resistance. J. Diabetes Metab. Disord. 11 (1), 22 (2012).

    Google Scholar 

  41. Würtz, P. et al. Branched-chain and aromatic amino acids are predictors of insulin resistance in young adults. Diabetes Care. 36 (3), 648–655 (2013).

    Google Scholar 

  42. Lynch, C. J. & Adams, S. H. Branched-chain amino acids in metabolic signalling and insulin resistance. Nat. Rev. Endocrinol. 10 (12), 723–736 (2014).

    Google Scholar 

  43. Menni, C. et al. Biomarkers for type 2 diabetes and impaired fasting glucose using a nontargeted metabolomics approach. Diabetes 62 (12), 4270–4276 (2013).

    Google Scholar 

  44. Conte, C., Epstein, S. & Napoli, N. Insulin resistance and bone: a biological partnership. Acta Diabetol. 55 (4), 305–314 (2018).

    Google Scholar 

  45. Epstein, S., Defeudis, G., Manfrini, S., Napoli, N. & Pozzilli, P. Diabetes and disordered bone metabolism (diabetic osteodystrophy): time for recognition. Osteoporos. Int. 27 (6), 1931–1951 (2016).

    Google Scholar 

  46. Leslie, W. D., Rubin, M. R., Schwartz, A. V. & Kanis, J. A. Type 2 diabetes and bone. J. Bone Min. Res. 27 (11), 2231–2237 (2012).

    Google Scholar 

  47. Gilli, G., Moiraghi Ruggenini, A., Nani, E., Bottura, G. & Mastretta, L. Study of the fatty acid components of the triglyceride fraction of the blood in normal and thalassemic subjects, using gas chromatography. Arch. Sci. Med. (Torino). 134 (3), 293–300 (1977).

    Google Scholar 

  48. Zhan, Q. et al. The opposite effects of Antarctic Krill oil and arachidonic acid-rich oil on bone resorption in ovariectomized mice. Food Funct. 11 (8), 7048–7060 (2020).

    Google Scholar 

  49. Casado-Diaz, A., Santiago-Mora, R., Dorado, G. & Quesada-Gomez, J. M. The omega-6 arachidonic fatty acid, but not the omega-3 fatty acids, inhibits osteoblastogenesis and induces adipogenesis of human mesenchymal stem cells: potential implication in osteoporosis. Osteoporos. Int. 24 (5), 1647–1661 (2013).

    Google Scholar 

  50. Zheng, D. M. et al. Medium and long-chain acylcarnitine’s relation to lipid metabolism as potential predictors for diabetic cardiomyopathy: a metabolomic study. Lipids Health Dis. 20 (1), 151 (2021).

    Google Scholar 

  51. Schooneman, M. G., Vaz, F. M., Houten, S. M. & Soeters, M. R. Acylcarnitines: reflecting or inflicting insulin resistance? Diabetes 62 (1), 1–8 (2013).

    Google Scholar 

  52. Paapstel, K. et al. Metabolomic profiles of lipid metabolism, arterial stiffness and hemodynamics in male coronary artery disease patients. IJC Metab. Endocr. 11, 13–18 (2016).

    Google Scholar 

  53. Chen, H. et al. Comparative proteomics reveals that fatty acid metabolism is involved in myocardial adaptation to chronic hypoxic injury. PLoS One. 19 (6), e0305571 (2024).

    Google Scholar 

  54. Huang, Z. et al. CPT1A-mediated fatty acid oxidation promotes precursor osteoclast fusion in rheumatoid arthritis. Front. Immunol. 13, 838664 (2022).

    Google Scholar 

  55. Aleidi, S. M. et al. Lipidomics profiling of patients with low bone mineral density (LBMD). Int. J. Mol. Sci. 23, 19 (2022).

    Google Scholar 

  56. Ke, J. Y. et al. Iron overload induces apoptosis of murine preosteoblast cells via ROS and inhibition of AKT pathway. Oral Dis. 23 (6), 784–794 (2017).

    Google Scholar 

  57. Wang, L. et al. Deletion of ferroportin in murine myeloid cells increases iron accumulation and stimulates osteoclastogenesis in vitro and in vivo. J. Biol. Chem. 293 (24), 9248–9264 (2018).

    Google Scholar 

  58. Zhang, X. et al. Metabolomics insights into osteoporosis through association with bone mineral density. J. Bone Min. Res. (2021).

  59. Wang, J., Wang, Y., Zeng, Y. & Huang, D. Feature selection approaches identify potential plasma metabolites in postmenopausal osteoporosis patients. Metabolomics 18 (11), 86 (2022).

    Google Scholar 

  60. Aleidi, S. M. et al. A distinctive human metabolomics alteration associated with osteopenic and osteoporotic patients. Metabolites ;11(9). (2021).

  61. Mei, Z. et al. Association between the metabolome and bone mineral density in a Chinese population. EBioMedicine 62, 103111 (2020).

    Google Scholar 

  62. Piriyakhuntorn, P. et al. Melatonin supplementation alleviates bone mineral density decline and circulating oxidative stress in iron-overloaded thalassemia patients. J. Pineal Res. 77 (3), e70055 (2025).

    Google Scholar 

Download references

Funding

This research was supported by a research grant from OPS MHESI, TSRI, and Chiang Mai University (RGNS 64-072: P.P.); a grant from the Thai Society of Hematology (P.P.); the Mid-Career Research Grant from the National Research Council of Thailand (C.T.); the Distinguished Research Professor Grant from the National Research Council of Thailand (N42A660301: S.C.C); and a Chiang Mai University Center of Excellence Award (N.C.)

Author information

Authors and Affiliations

  1. Division of Hematology, Department of Internal Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand

    Pokpong Piriyakhuntorn, Adisak Tantiworawit & Piangrawee Niprapan

  2. Cardiac Electrophysiology Unit, Department of Physiology, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand

    Chanisa Thonusin & Nipon Chattipakorn

  3. Nueurophysiology Unit, Cardiac Electrophysiology Research and Training Center, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand

    Chanisa Thonusin, Wichwara Nawara, Nipon Chattipakorn & Siriporn C. Chattipakorn

  4. Center of Excellence in Cardiac Electrophysiology Research, Chiang Mai University, Chiang Mai, Thailand

    Chanisa Thonusin, Wichwara Nawara, Nipon Chattipakorn & Siriporn C. Chattipakorn

  5. Division of Nuclear Medicine, Department of Radiology, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand

    Tawika Kaewchur

  6. The Academy of Science, The Royal Society of Thailand, Bangkok, Thailand

    Nipon Chattipakorn

  7. Department of Oral Biology and Diagnostic Sciences, Faculty of Dentistry, Chiang Mai University, Chiang Mai, Thailand

    Siriporn C. Chattipakorn

Authors
  1. Pokpong Piriyakhuntorn
    View author publications

    Search author on:PubMed Google Scholar

  2. Adisak Tantiworawit
    View author publications

    Search author on:PubMed Google Scholar

  3. Piangrawee Niprapan
    View author publications

    Search author on:PubMed Google Scholar

  4. Chanisa Thonusin
    View author publications

    Search author on:PubMed Google Scholar

  5. Wichwara Nawara
    View author publications

    Search author on:PubMed Google Scholar

  6. Tawika Kaewchur
    View author publications

    Search author on:PubMed Google Scholar

  7. Nipon Chattipakorn
    View author publications

    Search author on:PubMed Google Scholar

  8. Siriporn C. Chattipakorn
    View author publications

    Search author on:PubMed Google Scholar

Contributions

P.P.: Conceptualization, methodology, formal analysis, investigation, writing-original draft, funding acquisition; S.C.: Conceptualization, writing-review and editing, supervision; A.T.: Conceptualization, writing-review and editing; P.N.: Methodology, investigation; C.T.: Methodology, formal analysis, writing-review and editing; W.N.: Investigation; T.K.: Investigation; N.C.: Writing-review & editing; All authors read and approved the final manuscript.

Corresponding author

Correspondence to Siriporn C. Chattipakorn.

Ethics declarations

Competing interests

The authors declare no competing interests.

Declaration of generative AI and AI-assisted technologies in the writing process

During the preparation of this work, the author(s) used ChatGPT 4o in order to improve readability and language. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the published article.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Piriyakhuntorn, P., Tantiworawit, A., Niprapan, P. et al. Prevalence of low bone mineral density and associated plasma metabolite alterations in thalassemia. Sci Rep (2026). https://doi.org/10.1038/s41598-025-34667-z

Download citation

  • Received: 10 September 2025

  • Accepted: 30 December 2025

  • Published: 03 January 2026

  • DOI: https://doi.org/10.1038/s41598-025-34667-z

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Keywords

  • Thalassemia
  • Bone mineral density
  • Osteoporosis
  • Prevalence
  • Metabolomics
  • Metabolites
Download PDF

Advertisement

Explore content

  • Research articles
  • News & Comment
  • Collections
  • Subjects
  • Follow us on Facebook
  • Follow us on Twitter
  • Sign up for alerts
  • RSS feed

About the journal

  • About Scientific Reports
  • Contact
  • Journal policies
  • Guide to referees
  • Calls for Papers
  • Editor's Choice
  • Journal highlights
  • Open Access Fees and Funding

Publish with us

  • For authors
  • Language editing services
  • Open access funding
  • Submit manuscript

Search

Advanced search

Quick links

  • Explore articles by subject
  • Find a job
  • Guide to authors
  • Editorial policies

Scientific Reports (Sci Rep)

ISSN 2045-2322 (online)

nature.com sitemap

About Nature Portfolio

  • About us
  • Press releases
  • Press office
  • Contact us

Discover content

  • Journals A-Z
  • Articles by subject
  • protocols.io
  • Nature Index

Publishing policies

  • Nature portfolio policies
  • Open access

Author & Researcher services

  • Reprints & permissions
  • Research data
  • Language editing
  • Scientific editing
  • Nature Masterclasses
  • Research Solutions

Libraries & institutions

  • Librarian service & tools
  • Librarian portal
  • Open research
  • Recommend to library

Advertising & partnerships

  • Advertising
  • Partnerships & Services
  • Media kits
  • Branded content

Professional development

  • Nature Awards
  • Nature Careers
  • Nature Conferences

Regional websites

  • Nature Africa
  • Nature China
  • Nature India
  • Nature Japan
  • Nature Middle East
  • Privacy Policy
  • Use of cookies
  • Legal notice
  • Accessibility statement
  • Terms & Conditions
  • Your US state privacy rights
Springer Nature

© 2026 Springer Nature Limited

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research