Skip to main content

Advertisement

SpringerLink
Log in

Association between fatty liver index and controlled attenuation parameters as markers of metabolic dysfunction-associated fatty liver disease and bone mineral density: observational and two-sample Mendelian randomization studies

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

Abstract

Summary

Previously observational studies did not draw a clear conclusion on the association between fatty liver diseases and bone mineral density (BMD).

Our large-scale studies revealed that MAFLD and hepatic steatosis had no causal effect on BMD, while some metabolic factors were correlated with BMD.

The findings have important implications for the relationship between fatty liver diseases and BMD, and may help direct the clinical management of MAFLD patients who experience osteoporosis and osteopenia.

Purpose

Liver and bone are active endocrine organs with several metabolic functions. However, the link between metabolic dysfunction-associated fatty liver disease (MAFLD) and bone mineral density (BMD) is contradictory.

Methods

Using the UK Biobank and National Health and Nutrition Examination Survey (NHANES) dataset, we investigated the association between MAFLD, steatosis, and BMD in the observational analysis. We performed genome-wide association analysis to identify single-nucleotide polymorphisms associated with MAFLD. Large-scale two-sample Mendelian randomization (TSMR) analyses examined the potential causal relationship between MAFLD, hepatic steatosis, or major comorbid metabolic factors, and BMD.

Results

After adjusting for demographic factors and body mass index, logistic regression analysis demonstrated a significant association between MAFLD and reduced heel BMD. However, this association disappeared after adjusting for additional metabolic factors. MAFLD was not associated with total body, femur neck, and lumbar BMD in the NHANES dataset. Magnetic resonance imaging-measured steatosis did not show significant associations with reduced total body, femur neck, and lumbar BMD in multivariate analysis. TSMR analyses indicated that MAFLD and hepatic steatosis were not associated with BMD. Among all MAFLD-related comorbid factors, overweight and type 2 diabetes showed a causal relationship with increased BMD, while waist circumference and hyperlipidemia had the opposite effect.

Conclusion

No causal effect of MAFLD and hepatic steatosis on BMD was observed in this study, while some metabolic factors were correlated with BMD. This has important implications for understanding the relationship between fatty liver disease and BMD, which may help direct the clinical management of MAFLD patients with osteoporosis.

Graphical Abstract

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

Similar content being viewed by others

Data Availability

The UK Biobank data in the observational analysis is available on application (www.ukbiobank.co.uk). This research was conducted under application number 92668. The NHANES data can be found here: www.cdc.gov/nchs/nhanes/. The GWAS summary data are publicly available.

Abbreviations

NAFLD:

Nonalcoholic fatty liver disease

T2D:

Type 2 diabetes

MAFLD:

Metabolic-associated fatty liver disease

BMD:

Bone mineral density

BMI:

Body mass index

MR:

Mendelian randomization

TSMR:

Two-sample Mendelian randomization

GWAS:

Genome-wide association study

NHANES:

National Health and Nutrition Examination Survey

UKBB:

UK Biobank

FLI:

Fatty liver index

MRI:

Magnetic resonance imaging

MRI-PDFF:

Proton density fat fraction

WC:

Waist circumference

HDL-C:

Plasma high–density lipoprotein cholesterol

DXA:

Dual-energy X-ray absorptiometry

SD:

Standard deviation

SNP:

Single nucleotide polymorphism

IV:

Instrumental variable

IVW:

Inverse variance weighted

HBA1c:

Glycated hemoglobin

LDL-C:

Plasma low–density lipoprotein cholesterol

CHO:

Plasma total cholesterol

TG:

Plasma triglycerides

GGT:

Triglycerides and gamma-glutamyl transferase

OR:

Odds ratio

CI:

Confidence interval

LogOR:

Log-transformed OR

DBP:

Diastolic blood pressure

SBP:

Systolic blood pressure

References

  1. Younossi Z, Anstee QM, Marietti M et al (2018) Global burden of NAFLD and NASH: trends, predictions, risk factors and prevention. Nat Rev Gastroenterol Hepatol 15(1):11–20

    Article  PubMed  Google Scholar 

  2. Muzurović E, Mikhailidis DP, Mantzoros C (2021) Non-alcoholic fatty liver disease, insulin resistance, metabolic syndrome and their association with vascular risk. Metabolism 119:154770

    Article  PubMed  Google Scholar 

  3. Yki-Järvinen H (2014) Non-alcoholic fatty liver disease as a cause and a consequence of metabolic syndrome. Lancet Diabetes Endocrinol 2(11):901–910

    Article  PubMed  Google Scholar 

  4. Eslam M, Sanyal AJ, George J (2020) MAFLD: a consensus-driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology 158(7):1999-2014.e1991

    Article  CAS  PubMed  Google Scholar 

  5. Eslam M, Newsome PN, Sarin SK et al (2020) A new definition for metabolic dysfunction-associated fatty liver disease: an international expert consensus statement. J Hepatol 73(1):202–209

    Article  PubMed  Google Scholar 

  6. Cummings SR, Melton LJ (2002) Epidemiology and outcomes of osteoporotic fractures. Lancet 359(9319):1761–1767

    Article  PubMed  Google Scholar 

  7. Chen DZ, Xu QM, Wu XX et al (2018) The combined effect of nonalcoholic fatty liver disease and metabolic syndrome on osteoporosis in postmenopausal females in Eastern China. Int J Endocrinol 2018:2314769

    Article  PubMed  PubMed Central  Google Scholar 

  8. Lin S, Huang J, Wang M et al (2020) Comparison of MAFLD and NAFLD diagnostic criteria in real world. Liver Int 40(9):2082–2089

    Article  PubMed  Google Scholar 

  9. Haukeland JW, Damås JK, Konopski Z et al (2006) Systemic inflammation in nonalcoholic fatty liver disease is characterized by elevated levels of CCL2. J Hepatol 44(6):1167–1174

    Article  CAS  PubMed  Google Scholar 

  10. Xie R, Liu M (2022) Relationship between non-alcoholic fatty liver disease and degree of hepatic steatosis and bone mineral density. Front Endocrinol (Lausanne) 13:857110

    Article  PubMed  Google Scholar 

  11. Pan B, Cai J, Zhao P et al (2022) Relationship between prevalence and risk of osteoporosis or osteoporotic fracture with non-alcoholic fatty liver disease: a systematic review and meta-analysis. Osteoporos Int 33(11):2275–2286

    Article  PubMed  Google Scholar 

  12. Shen Z, Cen L, Chen X et al (2020) Increased risk of low bone mineral density in patients with non-alcoholic fatty liver disease: a cohort study. Eur J Endocrinol 182(2):157–164

    Article  CAS  PubMed  Google Scholar 

  13. Mantovani A, Gatti D, Zoppini G et al (2019) Association between nonalcoholic fatty liver disease and reduced bone mineral density in children: a meta-analysis. Hepatology 70(3):812–823

    Article  CAS  PubMed  Google Scholar 

  14. Ciardullo S, Muraca E, Zerbini F et al (2021) NAFLD and liver fibrosis are not associated with reduced femoral bone mineral density in the general US population. J Clin Endocrinol Metab 106(8):e2856–e2865

    Article  PubMed  Google Scholar 

  15. Mantovani A, Dauriz M, Gatti D et al (2019) Systematic review with meta-analysis: non-alcoholic fatty liver disease is associated with a history of osteoporotic fractures but not with low bone mineral density. Aliment Pharmacol Ther 49(4):375–388

    Article  PubMed  Google Scholar 

  16. Xie R, Zhang Y, Yan T et al (2022) Relationship between nonalcoholic fatty liver disease and bone mineral density in adolescents. Medicine (Baltimore) 101(41):e31164

    Article  CAS  PubMed  Google Scholar 

  17. Bowden J, Holmes MV (2019) Meta-analysis and Mendelian randomization: a review. Res Synth Methods 10(4):486–496

    Article  PubMed  PubMed Central  Google Scholar 

  18. Bedogni G, Bellentani S, Miglioli L et al (2006) The Fatty Liver Index: a simple and accurate predictor of hepatic steatosis in the general population. BMC Gastroenterol 6:33

    Article  PubMed  PubMed Central  Google Scholar 

  19. Caussy C, Reeder SB, Sirlin CB et al (2018) Noninvasive, quantitative assessment of liver fat by MRI-PDFF as an endpoint in NASH Trials. Hepatology 68(2):763–772

    Article  PubMed  Google Scholar 

  20. Eddowes PJ, Sasso M, Allison M et al (2019) Accuracy of FibroScan controlled attenuation parameter and liver stiffness measurement in assessing steatosis and fibrosis in patients with nonalcoholic fatty liver disease. Gastroenterology 156(6):1717–1730

    Article  PubMed  Google Scholar 

  21. Jiang L, Zheng Z, Fang H et al (2021) A generalized linear mixed model association tool for biobank-scale data. Nat Genet 53(11):1616–1621

    Article  CAS  PubMed  Google Scholar 

  22. Speliotes EK, Yerges-Armstrong LM, Wu J et al (2011) Genome-wide association analysis identifies variants associated with nonalcoholic fatty liver disease that have distinct effects on metabolic traits. PLoS Genet 7(3):e1001324

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Morris JA, Kemp JP, Youlten SE et al (2019) An atlas of genetic influences on osteoporosis in humans and mice. Nat Genet 51(2):258–266

    Article  CAS  PubMed  Google Scholar 

  24. Medina-Gomez C, Kemp JP, Trajanoska K et al (2018) Life-course genome-wide association study meta-analysis of total body BMD and assessment of age-specific effects. Am J Hum Genet 102(1):88–102

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Mahajan A, Wessel J, Willems SM et al (2018) Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes. Nat Genet 50(4):559–571

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Berndt SI, Gustafsson S, Mägi R et al (2013) Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture. Nat Genet 45(5):501–512

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Shungin D, Winkler TW, Croteau-Chonka DC et al (2015) New genetic loci link adipose and insulin biology to body fat distribution. Nature 518(7538):187–196

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Willer CJ, Schmidt EM, Sengupta S et al (2013) Discovery and refinement of loci associated with lipid levels. Nat Genet 45(11):1274–1283

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Manning AK, Hivert MF, Scott RA et al (2012) A genome-wide approach accounting for body mass index identifies genetic variants influencing fasting glycemic traits and insulin resistance. Nat Genet 44(6):659–669

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Evangelou E, Warren HR, Mosen-Ansorena D et al (2018) Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits. Nat Genet 50(10):1412–1425

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Papadimitriou N, Dimou N, Tsilidis KK et al (2020) Physical activity and risks of breast and colorectal cancer: a Mendelian randomisation analysis. Nat Commun 11(1):597

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Lee SJ, Lee JY, Sung J (2019) Obesity and bone health revisited: a Mendelian randomization study for Koreans. J Bone Miner Res 34(6):1058–1067

    Article  CAS  PubMed  Google Scholar 

  33. Chen HJ, Yang HY, Hsueh KC et al (2018) Increased risk of osteoporosis in patients with nonalcoholic fatty liver disease: a population-based retrospective cohort study. Medicine (Baltimore) 97(42):e12835

    Article  PubMed  Google Scholar 

  34. Ahn SH, Seo DH, Kim SH et al (2018) The relationship between fatty liver index and bone mineral density in Koreans: KNHANES 2010–2011. Osteoporos Int 29(1):181–190

    Article  CAS  PubMed  Google Scholar 

  35. Wang Y, Wen G, Zhou R et al (2018) Association of nonalcoholic fatty liver disease with osteoporotic fractures: a cross-sectional retrospective study of Chinese individuals. Front Endocrinol (Lausanne) 9:408

    Article  PubMed  Google Scholar 

  36. Upala S, Jaruvongvanich V, Wijarnpreecha K et al (2017) Nonalcoholic fatty liver disease and osteoporosis: a systematic review and meta-analysis. J Bone Miner Metab 35(6):685–693

    Article  CAS  PubMed  Google Scholar 

  37. Lee DY, Park JK, Hur KY et al (2018) Association between nonalcoholic fatty liver disease and bone mineral density in postmenopausal women. Climacteric 21(5):498–501

    Article  PubMed  Google Scholar 

  38. Polyzos SA, Anastasilakis AD, Kountouras J et al (2016) Circulating sclerostin and Dickkopf-1 levels in patients with nonalcoholic fatty liver disease. J Bone Miner Metab 34(4):447–456

    Article  CAS  PubMed  Google Scholar 

  39. Wang N, Chen C, Zhao L et al (2018) Vitamin D and nonalcoholic fatty liver disease: bi-directional mendelian randomization analysis. EBioMedicine 28:187–193

    Article  PubMed  PubMed Central  Google Scholar 

  40. Yuan S, Larsson SC (2023) Inverse association between serum 25-hydroxyvitamin D and nonalcoholic fatty liver disease. Clin Gastroenterol Hepatol 21(2):398–405.e394

  41. Zhou H, Li C, Song W et al (2021) Increasing fasting glucose and fasting insulin associated with elevated bone mineral density-evidence from cross-sectional and MR studies. Osteoporos Int 32(6):1153–1164

    Article  CAS  PubMed  Google Scholar 

  42. Walsh JS, Vilaca T (2017) Obesity, type 2 diabetes and bone in adults. Calcif Tissue Int 100(5):528–535

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Guañabens N, Parés A (2018) Osteoporosis in chronic liver disease. Liver Int 38(5):776–785

    Article  PubMed  Google Scholar 

  44. Wang Y, Dai J, Zhong W et al (2018) Association between serum cholesterol level and osteoporotic fractures. Front Endocrinol (Lausanne) 9:30

    Article  PubMed  Google Scholar 

  45. Castera L, Friedrich-Rust M, Loomba R (2019) Noninvasive assessment of liver disease in patients with nonalcoholic fatty liver disease. Gastroenterology 156(5):1264-1281.e1264

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

This research has been conducted using the UK Biobank (under application number 92668) and NHANES resource. We thank all the participants for their selfless contributions to the study. We thank all the genetics consortiums for making the GWAS summary data publicly available.

Funding

This work was supported by National Key Research and Development Program of China (No.2021YFC2500805, 2020YFC2006400), the National Nature Science Foundation of China (No.81972897,82172751), Guangzhou Science and Technology Project (No.202201011183), and GuangDong Basic and Applied Basic Research Foundation (No.2022A1515110656). This research has been conducted using the UK Biobank (under application number 92668) and NHANES resource. We thank all the participants for their selfless contributions to the study. We thank all the genetics consortiums for making the GWAS summary data publicly available.

Author information

Author notes

  1. Lin Zeng, Yan Li, Chang Hong, Jiaren Wang, and Hongbo Zhu contributed equally to this work

Authors and Affiliations

  1. Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China

    Lin Zeng, Yan Li, Chang Hong, Jiaren Wang, Qimei Li, Hao Cui, Ruining Li, Jingzhe He, Li Liu & Lushan Xiao

  2. Big Data Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China

    Lin Zeng, Pengcheng Ma & Li Liu

  3. Department of Medical Oncology, the First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, 421001, Hunan Province, China

    Hongbo Zhu

  4. Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China

    Hong Zhu

Authors
  1. Lin Zeng
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yan Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Chang Hong
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jiaren Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Hongbo Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Qimei Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Hao Cui
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Pengcheng Ma
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Ruining Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Jingzhe He
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Hong Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Li Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Lushan Xiao
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Hong Zhu, Li Liu or Lushan Xiao.

Ethics declarations

Ethics approval

All procedures performed involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1975 Declaration of Helsinki and its later amendments or comparable ethical standards. Ethical approval was granted for the UK Biobank by the North West-Haydock Research Ethics Committee (REC reference: 16/NW/0274). This study was conducted using the UK Biobank resource under application number 92668.

Patient consent

All participants provided informed consent at baseline assessment in the UK Biobank and NHANES datasets.

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

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

Zeng, L., Li, Y., Hong, C. et al. Association between fatty liver index and controlled attenuation parameters as markers of metabolic dysfunction-associated fatty liver disease and bone mineral density: observational and two-sample Mendelian randomization studies. Osteoporos Int 35, 679–689 (2024). https://doi.org/10.1007/s00198-023-06996-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00198-023-06996-0

Keywords

Search

Navigation