Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 Jun 25;116(1):89.
doi: 10.1007/s00223-025-01399-1.

Identification and Validation of Novel Lipids Linked to Bone Mineral Density Change and Fracture Risk

Affiliations

Identification and Validation of Novel Lipids Linked to Bone Mineral Density Change and Fracture Risk

Canchen Ma et al. Calcif Tissue Int. .

Abstract

To identify and validate lipid metabolites associated with bone mineral density (BMD) change and fracture risk through integrated Mendelian randomization (MR) and observational analyses. Two-sample MR analysis was first performed to uncover potential causal relationships between 32 lipid classes and 576 lipid species and BMD and fractures. Identified signatures were subsequently validated in an independent cohort (N = 492), where lipids, BMD, and fracture status were measured at two time points, 8 years apart. The false discovery rate method was employed to control multiple testing. Linear and log binomial mixed-effects models were used to analyze lipid associations with hip BMD and fracture risk, respectively. Two-sample MR revealed seven lipid classes causally associated with BMD and/or fractures, including acylcarnitine (AC), cholesteryl ester (CE), sphingomyelin (SM), phosphatidylinositol (PI), GM3 ganglioside (GM3), alkylphosphatidylcholine (PC(O)) and triacylglycerol (TG). Causal associations were found between 18 lipid species across these classes and BMD, and 10 lipid species were associated with fractures. Validation in an independent longitudinal cohort confirmed associations for total SM, SM(d18:1/16:0), SM(d18:2/24:0), and CE(18:3) with hip BMD change (β ranging from - 0.036 to - 0.012 g/cm2, per log µM increase, p < 1.13 × 10-2). Total SM, total GM3, and SM(d18:2/18:1), SM(d18:2/22:0), SM(d18:2/17:0) were associated with an increased risk of fractures (RR ranging from 1.038 to 1.290 g/cm2, per log µM increase, p < 5 × 10-2) over 8 years. Our findings suggest that alterations in lipid metabolism play a causal role in bone remodeling and fracture risk. This warrants further investigation into the mechanisms of lipid-mediated BMD changes and the potential for identifying patients at 'high risk' of osteoporotic fracture.

Keywords: Bone mineral density; Fracture; Lipids; Mendelian randomization.

PubMed Disclaimer

Conflict of interest statement

Declarations. Conflicts of interest: Canchen Ma, Ziyuan Shen, Jing Tian, Yvette L. Schooneveldt, Corey Giles, Flavia Cicuttini, Graeme Jones, Peter J. Meikle, and Feng Pan declare that they have no conflict of interest. Ethics approval and consent to participate: This study was approved by the Southern Tasmanian Health and Medical Human Research Ethics Committee (Ref. no: H0006488), and written informed consent was obtained from all participants. Graphical abstract: This study explores the causal relationship between lipid metabolism and changes in bone mineral density (BMD) and fracture risk through integrated two-sample Mendelian randomization (MR) and observational analysis. The two-sample MR analysis uncovers causal relationships between lipid classes and species with BMD and fractures. Validation in an independent cohort confirms associations for specific lipid species with hip BMD change and fracture risk over an 8-year period. These findings suggest lipid metabolism influences bone remodeling and fracture risk, highlighting the potential for targeted interventions and risk assessment in fracture prevention.

Figures

Fig. 1
Fig. 1
Flowchart of this study design. MR: Mendelian Randomization; BMD: Bone Mineral Density; GWAS: Genome-Wide Association Study; SNP: Single Nucleotide Polymorphism; IVW: Inverse-Variance Weighted; FDR: False Discovery Rate; TASOAC: Tasmanian Older Adult Cohort; LC–MS/MS: Liquid Chromatography–Tandem Mass Spectrometry
Fig. 2
Fig. 2
MR analyses at lipid class-level. A. Forest plot of MR estimates for the association between lipid classes and bone mineral density. B. Forest plot of MR estimates for associations between lipid classes and fracture risk. SNP: Single Nucleotide Polymorphism; CI: Confidence Interval; OR: Odds Ratio; IVW: Inverse-Variance Weighted; AC: Acylcarnitine; SM: Sphingomyelin; CE: Cholesteryl ester; PI: Phosphatidylinositol; GM3: GM3 ganglioside; PC(O): Alkylphosphatidylcholine; SM: Sphingomyelin; TG [NL]: Triacylglycerol (neutral loss, for associations)
Fig. 3
Fig. 3
MR analyses at lipid species-level. A Forest plot of MR estimates for associations between lipid species and bone mineral density. B Forest plot of MR estimates for associations between lipid species and fracture risk. SNP: Single Nucleotide Polymorphism; CI: Confidence Interval; OR: Odds Ratio; IVW: Inverse-Variance Weighted; AC: Acylcarnitine; SM: Sphingomyelin; CE: Cholesteryl ester; PI: Phosphatidylinositol; GM3: GM3 ganglioside; PC(O): Alkylphosphatidylcholine; SM: Sphingomyelin; TG [NL]: Triacylglycerol (neutral loss, for associations)
Fig. 3
Fig. 3
MR analyses at lipid species-level. A Forest plot of MR estimates for associations between lipid species and bone mineral density. B Forest plot of MR estimates for associations between lipid species and fracture risk. SNP: Single Nucleotide Polymorphism; CI: Confidence Interval; OR: Odds Ratio; IVW: Inverse-Variance Weighted; AC: Acylcarnitine; SM: Sphingomyelin; CE: Cholesteryl ester; PI: Phosphatidylinositol; GM3: GM3 ganglioside; PC(O): Alkylphosphatidylcholine; SM: Sphingomyelin; TG [NL]: Triacylglycerol (neutral loss, for associations)

Similar articles

References

    1. Marshall D, Johnell O, Wedel H (1996) Meta-analysis of how well measures of bone mineral density predict occurrence of osteoporotic fractures. BMJ 312(7041):1254–1259 - PMC - PubMed
    1. Clynes MA, Harvey NC, Curtis EM, Fuggle NR, Dennison EM, Cooper C (2020) The epidemiology of osteoporosis. Br Med Bull 133(1):105–117 - PMC - PubMed
    1. Kim BJ, Lee SH, Koh JM (2020) Potential biomarkers to improve the prediction of osteoporotic fractures. Endocrinol Metabol (Seoul, Korea) 35(1):55–63 - PMC - PubMed
    1. Park SG, Jeong SU, Lee JH, Ryu SH, Jeong HJ, Sim YJ et al (2018) The changes of CTX, DPD, osteocalcin, and bone mineral density during the postmenopausal period. Ann Rehabil Med 42(3):441–448 - PMC - PubMed
    1. Chen YN, Wei P, Yu B, Jian S (2019) Higher concentration of serum C-terminal cross-linking telopeptide of type I collagen is positively related with inflammatory factors in postmenopausal women with H-type hypertension and osteoporosis. Orthopaedc Surgery. 11(6):1135–1141 - PMC - PubMed