Skip to main content
SpringerLink
Log in

Cross-sectional studies of the causal link between asthma and osteoporosis: insights from Mendelian randomization and bioinformatics analysis

  • Original Article
  • Published:
Osteoporosis International Aims and scope Submit manuscript

Abstract

Summary

The study, using data from Chongqing, China, and employing Mendelian randomization along with bioinformatics, establishes a causal link between asthma and osteoporosis, beyond glucocorticoid effects. Asthma may contribute to osteoporosis by accelerating bone turnover through inflammatory factors, disrupting the coupling between osteoblasts and osteoclasts, ultimately leading to osteoporosis.

Introduction

Asthma and osteoporosis are prevalent health conditions with substantial public health implications. However, their potential interplay and the underlying mechanisms have not been fully elucidated. Previous research has primarily focused on the impact of glucocorticoids on osteoporosis, often overlooking the role of asthma itself.

Methods

We conducted a multi-stage stratified random sampling in Chongqing, China and excluded individuals with a history of glucocorticoid use. Participants underwent comprehensive health examinations, and their clinical data, including asthma status, were recorded. Logistic regression and Mendelian randomization were employed to investigate the causal link between asthma and osteoporosis. Furthermore, bioinformatics analyses and serum biomarker assessments were conducted to explore potential mechanistic pathways.

Results

We found a significant association between asthma and osteoporosis, suggesting a potential causal link. Mendelian Randomization analysis provided further support for this causal link. Bioinformatics analyses revealed that several molecular pathways might mediate the impact of asthma on bone health. Serum alkaline phosphatase levels were significantly elevated in the asthma group, suggesting potential involvement in bone turnover.

Conclusion

Our study confirms a causal link between asthma and osteoporosis and highlights the importance of considering asthma in osteoporosis prediction models. It also suggests that asthma may accelerate osteoporosis by increasing bone turnover through inflammatory factors, disrupting the coupling between osteoblasts and osteoclasts, ultimately leading to bone loss.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Data Availability

Due to privacy considerations for the surveyed population, the cross-sectional survey data used in this article are not publicly available. The asthma GWAS data utilized in this study were sourced from the GWAS Catalog(https://www.ebi.ac.uk/gwas/), while the osteoporosis GWAS data were obtained from the FinnGen consortium. Both sets of GWAS data mentioned above originate from freely accessible databases, with registration required for accessing data from the FinnGen consortium.

References

  1. Compston JE, McClung MR, Leslie WD (2019) Osteoporosis. Lancet Lond Engl 393:364–376. https://doi.org/10.1016/S0140-6736(18)32112-3

    Article  CAS  Google Scholar 

  2. Sims NA, Ng KW (2014) Implications of osteoblast-osteoclast interactions in the management of osteoporosis by antiresorptive agents denosumab and odanacatib. Curr Osteoporos Rep 12:98–106. https://doi.org/10.1007/s11914-014-0196-1

    Article  PubMed  Google Scholar 

  3. Song S, Guo Y, Yang Y, Fu D (2022) Advances in pathogenesis and therapeutic strategies for osteoporosis. Pharmacol Ther 237:108168. https://doi.org/10.1016/j.pharmthera.2022.108168

    Article  CAS  PubMed  Google Scholar 

  4. Mundy GR (2007) Osteoporosis and inflammation. Nutr Rev 65:S147-151. https://doi.org/10.1111/j.1753-4887.2007.tb00353.x

    Article  PubMed  Google Scholar 

  5. Tao H, Li W, Zhang W et al (2021) Urolithin A suppresses RANKL-induced osteoclastogenesis and postmenopausal osteoporosis by, suppresses inflammation and downstream NF-κB activated pyroptosis pathways. Pharmacol Res 174:105967. https://doi.org/10.1016/j.phrs.2021.105967

    Article  CAS  PubMed  Google Scholar 

  6. Zhang S, Ni W (2023) High systemic immune-inflammation index is relevant to osteoporosis among middle-aged and older people: a cross-sectional study. Immun Inflamm Dis 11:e992. https://doi.org/10.1002/iid3.992

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Papi A, Brightling C, Pedersen SE, Reddel HK (2018) Asthma. Lancet Lond Engl 391:783–800. https://doi.org/10.1016/S0140-6736(17)33311-1

    Article  Google Scholar 

  8. Huang K, Yang T, Xu J et al (2019) Prevalence, risk factors, and management of asthma in China: a national cross-sectional study. Lancet Lond Engl 394:407–418. https://doi.org/10.1016/S0140-6736(19)31147-X

    Article  Google Scholar 

  9. Chalitsios CV, McKeever TM, Shaw DE (2021) Incidence of osteoporosis and fragility fractures in asthma: a UK population-based matched cohort study. Eur Respir J 57:2001251. https://doi.org/10.1183/13993003.01251-2020

    Article  PubMed  Google Scholar 

  10. Ora J, Calzetta L, Matera MG et al (2020) Advances with glucocorticoids in the treatment of asthma: state of the art. Expert Opin Pharmacother 21:2305–2316. https://doi.org/10.1080/14656566.2020.1807514

    Article  CAS  PubMed  Google Scholar 

  11. Oh JY, Lee YS, Min KH et al (2018) Osteoporosis in patients with asthma-chronic obstructive pulmonary disease overlap syndrome. Tuberc Respir Dis 81:73–79. https://doi.org/10.4046/trd.2017.0066

    Article  Google Scholar 

  12. Jv F (2015) Type 2 inflammation in asthma—present in most, absent in many. Nat Rev Immunol 15. https://doi.org/10.1038/nri3786

  13. Woodruff PG, Modrek B, Choy DF et al (2009) T-helper type 2-driven inflammation defines major subphenotypes of asthma. Am J Respir Crit Care Med 180:388–395. https://doi.org/10.1164/rccm.200903-0392OC

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Habib N, Pasha MA, Tang DD (2022) Current understanding of asthma pathogenesis and biomarkers. Cells 11:2764. https://doi.org/10.3390/cells11172764

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Akar-Ghibril N, Casale T, Custovic A, Phipatanakul W (2020) Allergic endotypes and phenotypes of asthma. J Allergy Clin Immunol Pract 8:429–440. https://doi.org/10.1016/j.jaip.2019.11.008

    Article  PubMed  PubMed Central  Google Scholar 

  16. Sekula P, Del Greco MF, Pattaro C, Köttgen A (2016) Mendelian randomization as an approach to assess causality using observational data. J Am Soc Nephrol JASN 27:3253–3265. https://doi.org/10.1681/ASN.2016010098

    Article  PubMed  Google Scholar 

  17. Ference BA, Holmes MV, Smith GD (2021) Using Mendelian randomization to improve the design of randomized trials. Cold Spring Harb Perspect Med 11:a040980. https://doi.org/10.1101/cshperspect.a040980

    Article  PubMed  PubMed Central  Google Scholar 

  18. Birney E (2022) Mendelian randomization. Cold Spring Harb Perspect Med 12:a041302. https://doi.org/10.1101/cshperspect.a041302

    Article  PubMed  Google Scholar 

  19. Bowden J, Holmes MV (2019) Meta-analysis and Mendelian randomization: a review. Res Synth Methods 10:486–496. https://doi.org/10.1002/jrsm.1346

    Article  PubMed  PubMed Central  Google Scholar 

  20. Yang J, Sun J, Luo F et al (2011) Peak BMD assessment in a Chinese infantry recruit group. Int J Sports Med 32:970–974. https://doi.org/10.1055/s-0031-1283191

    Article  CAS  PubMed  Google Scholar 

  21. The Division of Osteoporosis and Mineral Diseases of the Chinese Medical Association (2022) Diagnosis and treatment guidelines for primary osteoporosis. Chin J Osteoporos Bone Miner Res 15(6):573–610. https://doi.org/10.3969/j.issn.1674-2591.2022.06.001

    Article  Google Scholar 

  22. Zhu Z, Zhu X, Liu C-L et al (2019) Shared genetics of asthma and mental health disorders: a large-scale genome-wide cross-trait analysis. Eur Respir J 54:1901507. https://doi.org/10.1183/13993003.01507-2019

    Article  PubMed  Google Scholar 

  23. Kurki MI, Karjalainen J, Palta P et al (2023) FinnGen provides genetic insights from a well-phenotyped isolated population. Nature 613:508–518. https://doi.org/10.1038/s41586-022-05473-8

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  24. Wang L, Li X, Montazeri A et al (2023) Phenome-wide association study of genetically predicted B vitamins and homocysteine biomarkers with multiple health and disease outcomes: analysis of the UK Biobank. Am J Clin Nutr 117:564–575. https://doi.org/10.1016/j.ajcnut.2023.01.005

    Article  CAS  PubMed  Google Scholar 

  25. Shannon P, Markiel A, Ozier O et al (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 13:2498–2504. https://doi.org/10.1101/gr.1239303

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Kearney DM, Lockey RF (2006) Osteoporosis and asthma. Ann Allergy Asthma Immunol Off Publ Am Coll Allergy Asthma Immunol 96:769–774. quiz 775–778, 857. https://doi.org/10.1016/S1081-1206(10)61338-5

    Article  Google Scholar 

  27. Jackson DJ, Bacharier LB, Mauger DT et al (2018) Quintupling inhaled glucocorticoids to prevent childhood asthma exacerbations. N Engl J Med 378:891–901. https://doi.org/10.1056/NEJMoa1710988

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Bardin PG (2018) Inhaled glucocorticoids in asthma. N Engl J Med 378:2052. https://doi.org/10.1056/NEJMc1804801

    Article  PubMed  Google Scholar 

  29. Lane NE (2019) Glucocorticoid-induced osteoporosis: new insights into the pathophysiology and treatments. Curr Osteoporos Rep 17:1–7. https://doi.org/10.1007/s11914-019-00498-x

    Article  PubMed  PubMed Central  Google Scholar 

  30. Gaziano L, Sun L, Arnold M et al (2022) Mild-to-moderate kidney dysfunction and cardiovascular disease: observational and mendelian randomization analyses. Circulation 146:1507–1517. https://doi.org/10.1161/CIRCULATIONAHA.122.060700

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Skrivankova VW, Richmond RC, Woolf BAR et al (2021) Strengthening the reporting of observational studies in epidemiology using Mendelian randomization: the STROBE-MR statement. JAMA 326:1614–1621. https://doi.org/10.1001/jama.2021.18236

    Article  PubMed  Google Scholar 

  32. Enríquez-Matas A, Fernández-Rodríguez C, Andrés Esteban EM, Fernández-Crespo J (2020) Main contributory factors on asthma control and health-related quality of life in elderly asthmatics. J Investig Allergol Clin Immunol 30:264–271

    Article  PubMed  Google Scholar 

  33. Li P, Ghazala L, Wright E et al (2015) Prevalence of osteopenia and osteoporosis in patients with moderate to severe asthma in Western Canada. Clin Investig Med Med Clin Exp 38:E23–E30

    Article  Google Scholar 

  34. To Y, Taguchi Y, Shimazaki T et al (2021) Real-world treatment and health care resource use among severe asthma patients in Japan. Respir Investig 59:464–477. https://doi.org/10.1016/j.resinv.2021.02.010

    Article  PubMed  Google Scholar 

  35. Ji J, Hemminki K, Sundquist K, Sundquist J (2010) Seasonal and regional variations of asthma and association with osteoporosis: possible role of vitamin D in asthma. J Asthma Off J Assoc Care Asthma 47:1045–1048. https://doi.org/10.1080/02770903.2010.508553

    Article  Google Scholar 

  36. Jo E-J, Lee YU, Kim A et al (2023) The prevalence of multiple chronic conditions and medical burden in asthma patients. PLoS ONE 18:e0286004. https://doi.org/10.1371/journal.pone.0286004

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Cazzola M, Calzetta L, Bettoncelli G et al (2011) Asthma and comorbid medical illness. Eur Respir J 38:42–49. https://doi.org/10.1183/09031936.00140310

    Article  CAS  PubMed  Google Scholar 

  38. Lane NE (2006) Epidemiology, etiology, and diagnosis of osteoporosis. Am J Obstet Gynecol 194:S3-11. https://doi.org/10.1016/j.ajog.2005.08.047

    Article  CAS  PubMed  Google Scholar 

  39. Eastell R, Szulc P (2017) Use of bone turnover markers in postmenopausal osteoporosis. Lancet Diabetes Endocrinol 5:908–923. https://doi.org/10.1016/S2213-8587(17)30184-5

    Article  PubMed  Google Scholar 

  40. Mukaiyama K, Kamimura M, Uchiyama S et al (2015) Elevation of serum alkaline phosphatase (ALP) level in postmenopausal women is caused by high bone turnover. Aging Clin Exp Res 27:413–418. https://doi.org/10.1007/s40520-014-0296-x

    Article  PubMed  Google Scholar 

  41. Nawawi HM, Yazid TN, Ismail NM et al (2001) Serum bone specific alkaline phosphatase and urinary deoxypyridinoline in postmenopausal osteoporosis. Malays J Pathol 23:79–88

    CAS  PubMed  Google Scholar 

  42. Schini M, Vilaca T, Gossiel F et al (2023) Bone turnover markers: basic biology to clinical applications. Endocr Rev 44:417–473. https://doi.org/10.1210/endrev/bnac031

    Article  PubMed  Google Scholar 

  43. Jain S, Camacho P (2018) Use of bone turnover markers in the management of osteoporosis. Curr Opin Endocrinol Diabetes Obes 25:366–372. https://doi.org/10.1097/MED.0000000000000446

    Article  PubMed  Google Scholar 

  44. Fricker M, Gibson PG, Powell H et al (2019) A sputum 6-gene signature predicts future exacerbations of poorly controlled asthma. J Allergy Clin Immunol 144:51-60.e11. https://doi.org/10.1016/j.jaci.2018.12.1020

    Article  CAS  PubMed  Google Scholar 

  45. Yokoi K, Nakajima Y, Shinkai Y et al (2019) Clinical and genetic aspects of mild hypophosphatasia in Japanese patients. Mol Genet Metab Rep 21:100515. https://doi.org/10.1016/j.ymgmr.2019.100515

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. de Andrade KR, de Castro GRW, Vicente G et al (2014) Evaluation of circulating levels of inflammatory and bone formation markers in axial spondyloarthritis. Int Immunopharmacol 21:481–486. https://doi.org/10.1016/j.intimp.2014.05.031

    Article  CAS  PubMed  Google Scholar 

  47. Shead EF, Haworth CS, Barker H et al (2010) Osteoclast function, bone turnover and inflammatory cytokines during infective exacerbations of cystic fibrosis. J Cyst Fibros Off J Eur Cyst Fibros Soc 9:93–98. https://doi.org/10.1016/j.jcf.2009.11.007

    Article  CAS  Google Scholar 

  48. Fischer V, Haffner-Luntzer M (2022) Interaction between bone and immune cells: implications for postmenopausal osteoporosis. Semin Cell Dev Biol 123:14–21. https://doi.org/10.1016/j.semcdb.2021.05.014

    Article  PubMed  Google Scholar 

  49. Wang T, He C (2020) TNF-α and IL-6: the Link between immune and bone system. Curr Drug Targets 21:213–227. https://doi.org/10.2174/1389450120666190821161259

    Article  CAS  PubMed  Google Scholar 

Download references

Funding

This work was supported by (1) The project of enhance scientific and technological innovation capacity (No. 2019XLC2015), (2) National Key R&D Program of China (No. 2018YFA0800802).

Author information

Author notes

  1. Lexin Chen and Can Li contributed equally to this work.

Authors and Affiliations

  1. Center of Osteoporosis and Bone Development, Laboratory of Injury Repair and Rehabilitation Medicine, State Key Laboratory of Trauma and Chemical Poisoning, Daping Hospital, Army Medical University, Chongqing, 400042, China

    Lexin Chen, Can Li, Hangang Chen, Yangli Xie, Nan Su, Fengtao Luo, Junlan Huang, Ruobin Zhang, Lin Chen, Bo Chen & Jing Yang

  2. Chongqing Medical University, Chongqing, 400010, China

    Lexin Chen & Hangang Chen

Authors
  1. Lexin Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Can Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hangang Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yangli Xie
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Nan Su
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Fengtao Luo
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Junlan Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Ruobin Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Lin Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Bo Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Jing Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Bo Chen or Jing Yang.

Ethics declarations

Ethics approval and consent to participate

The research protocol received approval from the Ethics Review Committee of the Chinese Center for Disease Control and Prevention. All study participants provided written informed consent, with confidentiality of information assured. This study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.

Conflicts of interest

None.

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 file1 (PDF 148 KB)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, L., Li, C., Chen, H. et al. Cross-sectional studies of the causal link between asthma and osteoporosis: insights from Mendelian randomization and bioinformatics analysis. Osteoporos Int (2024). https://doi.org/10.1007/s00198-024-07037-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s00198-024-07037-0

Keywords

Search

Navigation