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The diagnostic value of the combined application of blood lipid metabolism markers and interleukin-6 in osteoporosis and osteopenia

Lipids in Health and Disease volume 24, Article number: 38 (2025) Cite this article

Abstract

Background

This study aimed to analyse the relationship of the blood lipid profile and interleukin-6 (IL-6) with osteoporosis and osteopenia and to explore the predictive value of the combined application of these biomarkers in osteoporosis and osteopenia.

Methods

Data from 276 patients treated in the orthopaedics department were retrospectively analysed. Their general information was collected, and the relationships among the blood lipid profile, IL-6 with bone turnover markers, and bone mineral density (BMD) were analysed. Patients were categorized based on their T scores for intergroup comparisons. Finally, the diagnostic efficiency of lipid metabolism markers and IL-6 for osteoporosis and osteopenia was assessed using receiver operating characteristic (ROC) curves.

Results

(1) In both males and females, a negative relationship was observed between BMD and several biomarkers, including total cholesterol (TC), apolipoprotein B (ApoB), low-density lipoprotein cholesterol (LDL-C), free fatty acids (FFAs), and IL-6. Additionally, apolipoprotein A1 (ApoA1) was negatively correlated with BMD only in females, and the ApoA1/ApoB ratio was positively correlated with BMD only in males. (2) FFAs and IL-6 were positively correlated with β-CrossLaps peptide in males. However, for females, TC, ApoB, LDL-C, and IL-6 were negatively correlated with 25-hydroxyvitamin D. FFAs, IL-6, and age were negatively correlated with osteocalcin in males and females. (3) According to the T scores for the lumbar spine, the TC, ApoA1, ApoB, HDL-C, LDL-C, FFA, and IL-6 levels in the osteoporosis group and the TC, ApoB, LDL-C, and FFA levels in the osteopenia group were significantly greater than those in the normal bone mass group. Additionally, the osteoporosis group presented substantially higher levels of ApoA1, FFAs, and IL-6 than the osteopenia group. (4) IL-6 was positively correlated with FFAs, while a negative correlation was observed with TC, ApoA1, ApoB, HDL-C, and LDL-C. (5) The ROC curve revealed that the areas under the curve (AUCs) of TC, FFAs, IL-6, ApoA1, and the ApoA1/ApoB ratio for predicting osteoporosis or osteopenia were 0.634, 0.713, 0.670, 0.628, and 0.516, respectively, whereas the AUC of the combination of TC, FFAs, IL-6, and ApoA1 was 0.846, and the AUC of the combination of TC, FFAs, IL-6, and the ApoA1/ApoB ratio was 0.842. In the sex stratification analysis, in males, the AUCs of TC, FFAs, IL-6, and the ApoA1/ApoB ratio for the prediction of osteoporosis or osteopenia were 0.596, 0.688, 0.739, and 0.539, respectively. In contrast, the AUC of the combination of TC, FFAs, IL-6, and the ApoA1/ApoB ratio was 0.838. In females, the AUCs of TC, FFAs, IL-6, ApoA1, and the ApoA1/ApoB ratio for predicting osteoporosis or osteopenia were 0.620, 0.728, 0.653, 0.611, and 0.502, respectively, whereas the AUC of the combination of TC, FFAs, IL-6, and ApoA1 was 0.841, and the AUC of the combination of TC, FFAs, IL-6, and the ApoA1/ApoB ratio was 0.828.

Conclusion

The levels of TC, FFAs, IL-6, ApoA1, and ApoB could contribute to changes in bone metabolism, moreover, FFAs could induce an increase in IL-6 further aggravating bone mass loss and leading to osteoporosis. Based on the comparison of the AUC results, the combination of TC, FFAs, and IL-6 with ApoA1 or the ApoA1/ApoB ratio can better predict osteoporosis or osteopenia in patients, and the diagnostic efficiency is significantly better than that of any individual indicator. The regulation of blood lipid levels should become a new target for clinicians to treat osteoporosis and osteopenia.

Background

Osteoporosis (OP) is characterized by decreased bone mass, microstructure destruction of bone, and increased bone fragility [1, 2]. Its most serious complication is osteoporotic fracture, which clinically manifests as pain, spinal deformity, and fragility fracture; therefore, OP significantly affects patients' quality of life and longevity [3]. It is nicknamed the "silent killer" [4]. OP tends to worsen as the global population ages. In 2015, there were approximately 2.69 million new cases of osteoporotic fractures in China. This figure will increase to approximately 4.83 million by 2035 [5]. Therefore, effective measures to control and prevent the development of OP are urgently needed [6].

The pathological mechanism of OP is currently not yet clear, and the full process of bone matrix mineralization remains a mystery. A key feature of OP is decreased bone mineral density (BMD) [7]. OP is usually diagnosed via BMD measurements in the hip, lumbar spine, and other locations via dual-energy X-ray absorptiometry (DXA) [8]. However, the BMD can reflect only the combined effects of various factors acting on the bone and cannot reflect the metabolic changes in bone cells over time. Bone turnover markers (BTMs) are metabolites of bone tissue that exhibit rapid responses to physiological changes in bone and have greater accuracy and timeliness in reflecting changes in bone cell metabolism [9]. They are reliable predictors of bone loss and have contributed significantly to the diagnosis of OP and osteopenia [10, 11]. The N-terminal propeptide of type 1 procollagen (P1NP) is an important index of new bone formation. β-CrossLaps peptide (β-CTx) is an important bone metabolic index reflecting bone resorption and is the most widely used collagen degradation marker. Osteocalcin (OC) can directly reflect osteoblast activity and bone formation. 25-hydroxyvitamin D [25(OH)D] can regulate bone metabolism and calcium levels and exert immunomodulatory effects. These indicators are essential for the investigation of OP.

Patients with OP often have dyslipidaemia, and some studies have shown that lipid levels are related to the occurrence of OP [12]. Moreover, drugs for dyslipidaemia, such as statins, can also affect bone tissue [13]. Previous research has revealed a correlation between high blood lipid concentrations and an increased likelihood of developing OP as follows: (1) Adipocytes and osteoblasts, which are common cellular progenitors, both emerge through differentiation from bone marrow stromal stem cells [14]. Under certain circumstances, adipocytes and osteoblasts can transform into each other. In the bone marrow, an increased quantity of adipocytes leads to increased pressure in the cavity and decreased osteoblasts, eventually leading to OP and bone mass loss [13]. (2) Proinflammatory cytokines and lipids are implicated in osteoporosis pathogenesis. Adipocytes promote the secretion of proinflammatory cytokines, including IL-6, thereby influencing bone turnover and further reducing BMD [15]. (3) Research has shown that RANKL, which is expressed by adipocytes, is one of the most crucial regulatory molecules for osteoclasts and that PPAR-γ and its ligand expressed by adipocytes can stimulate the differentiation of osteoclasts and bone resorption [16].

There is also an interrelationship between the skeletal system and the immune response. Bone immunology includes not only the interaction between bone cells and lymphocytes but also the regulation of immune factors in bone [17]. IL-6 is an immune-derived cytokine that regulates osteoblasts, osteoclasts, bone marrow fat cells, and osteocytes [16].

Research exploring the links among the blood lipid profile, IL-6, and OP is scarce. Almost none of the previously published studies investigated the combination of the blood lipid profile and IL-6 in predicting OP. Therefore, this study involved a detailed sex stratification analysis and comprehensively analysed the intrinsic correlation of these indicators. This study suggested that the combined application of TC, FFAs, and IL-6 with ApoA1 or the ApoA1/ApoB ratio could better predict OP or osteopenia in patients and that the prediction effect was significantly better than that of any single indicator. This study will help improve the detection rate of early-stage OP and provide a new target for diagnosing and treating OP.

Research methods

Study population

Data from 276 patients who were over 20 years old and treated in the Department of Orthopaedics of The Second Affiliated Hospital of Zhejiang Chinese Medical University from December 2023 to August 2024 were retrospectively analysed. The mean age was 61.61±14.89 years, and 176 females and 100 males were included.

Exclusion criteria: (1) patients taking drugs long-term, such as glucocorticoids and active vitamin D, that affect bone metabolism; (2) patients with malignant tumors; (3) patients taking drugs long-term that affect lipid metabolism; (4) patients with serious endocrine diseases, such as those affecting the pituitary, thyroid and parathyroid glands; (5) patients with severe hereditary or congenital skeletal motor system diseases; and (6) patients with complete paralysis and inability to walk. The research obeyed the Helsinki Declaration, and the Ethics Committee of The Second Affiliated Hospital of Zhejiang Chinese Medicine University granted ethical clearance for this investigation (Approval No. 2024-LW-012-01).

Clinical data

Data for this study were collected from patients’ electronic medical records. Blood specimens from each patient were collected in the morning following an overnight fast. HDL-C, LDL-C, TG, TC, and FFAs were analysed via enzymatic assays. ApoA1 and ApoB were determined by immunoturbidimetry. P1NP, OC, 25(OH)D, and β-CTx were detected via chemiluminescence assays. IL-6 levels were determined by immunofluorescence.

BMD determination

BMD is considered one of the main indices for evaluating OP and osteopenia. An OSTEOCORE2 DXA bone densitometer (MEDIX DR) was utilized to measure the BMD of the hip and lumbar spine. The patients were categorized into three groups according to the WHO criteria: the OP group (T score ≤ -2.5), the osteopenia group (-1.0 > T score > -2.5), and the normal bone mass group (T score ≥ −1.0).

Statistical analysis

Data statistics were conducted using IBM SPSS Statistics version 26.0 and GraphPad Prism version 8.0. The Shapiro–Wilk test was adopted to determine whether the data were normally distributed. Data conforming to a normal distribution are presented as the means ± SDs, whereas data not following a normal distribution are depicted as [medians (IQRs P25, P75)]. Intergroup differences were calculated using the t test and ANOVA for normally distributed data. The Mann–Whitney U and Kruskal–Wallis tests were applied to calculate intergroup differences for nonnormally distributed data. Categorical indicators expressed in numbers and percentages were analysed via the chi-square method. The relationship between a dependent variable and one or more independent variables was analysed via linear regression analysis. ROC curves were generated to evaluate the diagnostic efficiency of single or combined indicators. A P value < 0.05 was deemed significant.

Results

Baseline analysis stratified by sex in this study

There was no notable variation in age between male and female patients. The BMD of females was lower than that of males. However, the TC, ApoA1, ApoA1/ApoB ratio and HDL-C levels were higher in females than in males (Table 1).

Table 1 Baseline characteristics of 276 patients stratified by sex
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Correlations of blood lipid profile and IL-6 with BTMs stratified by sex

Among all patients, β-CTx was positively correlated with FFAs and IL-6. OC was positively correlated with ApoA1 and TG and negatively correlated with FFAs, IL-6, and age. 25(OH)D was negatively correlated with TC, ApoB, LDL-C, IL-6, and age.

Further sex stratification analysis revealed that in male patients, β-CTx was positively correlated with FFAs and IL-6, and OC was positively correlated with TG; in female patients, 25(OH)D was negatively correlated with TC, ApoB, LDL-C, IL-6, and age; OC was negatively correlated with FFAs, IL-6, and age regardless of sex (Additional file 1: Table S1).

Correlations of blood lipid profile, IL-6, and BTMs with BMD stratified by sex

Among all patients, hip BMD and lumbar BMD showed positive correlations with 25(OH)D and negative correlations with TC, HDL-C, ApoA1, FFAs, IL-6, β-CTx, P1NP, and age. LDL-C and ApoB were negatively correlated with lumbar BMD, but no correlations were found with hip BMD. In addition, the ApoA1/ApoB ratio was negatively correlated with hip BMD, but no correlations were found with lumbar BMD.

Further sex stratification analysis revealed that in male patients, TC, LDL-C, and ApoB were negatively correlated with lumbar BMD, but no correlations were found with hip BMD. The ApoA1/ApoB ratio showed a positive correlation with lumbar BMD, but no correlation was found with hip BMD. β-CTx showed negative correlations with hip BMD and lumbar BMD and 25(OH)D showed a positive correlation with hip BMD. In female patients, OC showed a positive correlation with hip BMD, and 25(OH)D showed positive correlations with hip BMD and lumbar BMD. FFAs and IL-6 were negatively correlated with hip BMD and lumbar BMD regardless of sex (Additional file 2: Table S2).

Association of blood lipid profile and IL-6 with lumbar BMD stratified by sex

Linear regression analysis was applied to analyse the association of blood lipid profile and IL-6 with lumbar BMD. Model 1 was the model without adjustment for covariates, and Model 2 was the model after adjustment for the confounding factor of age.

In male patients, TC, LDL-C, ApoB, FFAs, and IL-6 showed negative associations with lumbar BMD, and the ApoA1/ApoB ratio was positively associated with lumbar BMD in both Model 1 and Model 2. In female patients, ApoA1 and FFAs were negatively associated with lumbar BMD in both Model 1 and Model 2, and IL-6 exhibited a negative association with lumbar BMD only in Model 1. Additionally, TC, LDL-C, and ApoB were inversely associated with lumbar BMD only in Model 2 (Table 2).

Table 2 Association of blood lipid profile and IL-6 with lumbar BMD stratified by sex
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Association of blood lipid profile and IL-6 with hip BMD stratified by sex

The association of blood lipid profile and IL-6 with hip BMD was analysed by linear regression. Model 1 was the model without adjustment for covariates, and Model 2 was the model after adjustment for the confounding factor of age.

In male patients, FFAs and IL-6 were negatively associated with hip BMD in both Model 1 and Model 2; in addition, TC and LDL-C were negatively associated with hip BMD only in Model 2. In female patients, FFAs and IL-6 were negatively associated with hip BMD in both Model 1 and Model 2; in addition, TC and ApoA1 were negatively associated with hip BMD only in Model 2 (Table 3).

Table 3 Association of blood lipid profile and IL-6 with hip BMD stratified by sex
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IL-6 is associated with various lipid metabolism markers

Linear regression analysis was utilized to analyse the association between IL-6 and various lipid metabolism markers. IL-6 was negatively correlated with TC, ApoA1, HDL-C, ApoB, and LDL-C, but positively correlated with FFAs (Table 4).

Table 4 IL-6 is associated with various lipid metabolism markers
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Blood lipid profile, IL-6, and patient features in the different groups

The patients were categorized into three groups based on their lumbar spine T scores. Notable intergroup differences were observed in TC, HDL-C, LDL-C, ApoA1, ApoB, FFA, and IL-6 levels (Fig. 1, Additional file 3: Table S3).

Fig. 1
figure 1

Changes in lipid metabolism indicators and IL-6 in groups according to lumbar spine T scores. *P<0.05, **P<0.01, ***P<0.001

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Similarly, with respect to hip T scores, notable intergroup differences were observed in ApoA1, FFA, and IL-6 levels (Fig. 2, Additional file 3: Table S3).

Fig. 2
figure 2

Changes in lipid metabolism indicators and IL-6 in groups according to hip T scores. *P<0.05, **P<0.01, ***P<0.001

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This study found relatively few patients with OP according to hip T scores. Since the patients’ hips are continuously subjected to more stress stimulation during daily life and work, according to Wolf's law, bone density and stiffness increase when subjected to external stress. As a result, in female patients, the mean BMD of the hips was notably greater than that of their lumbar spine (Additional file 4: Table S4).

Comprehensive analysis of the effects of various lipid metabolism markers and IL-6 on bone density

Multiple linear regression analysis was utilized to evaluate the ability of various lipid metabolism markers and IL-6 to predict bone density. TC, FFAs, IL-6, ApoA1, or the ApoA1/ApoB ratio, and age were included in the multifactor linear regression equation.

The results revealed that among all patients, TC, FFAs, IL-6, the ApoA1/ApoB ratio, and age were negatively associated with lumbar vertebral density and hip bone density.

In male patients, TC, FFAs, and IL-6 were negatively associated with lumbar vertebral density and hip bone density. In female patients, TC, FFA, IL-6, and ApoA1 levels and age were negatively associated with lumbar vertebral density, and ApoA1, FFA, and IL-6 levels and age were negatively associated with hip bone density (Table 5).

Table 5 Comprehensive analysis of the effects of various lipid metabolism markers and IL-6 on bone density
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Joint application of blood lipid metabolism markers and IL-6 for predicting the risk of OP or osteopenia in the lumbar spine

Using ROC curve analysis, the diagnostic efficiencies of TC, FFAs, IL-6, ApoA1, and the ApoA1/ApoB ratio and their combination on OP or osteopenia in the lumbar spine were assessed.

Among all patients, the optimal cut-off values for TC, FFAs, IL-6, ApoA1, and the ApoA1/ApoB ratio were 4.960, 0.527, 7.500, 1.345, and 1.462, respectively. The AUC of TC for predicting lumbar spine OP or osteopenia was 0.662, and the AUCs of FFAs IL-6, ApoA1, and the ApoA1/ApoB ratio were 0.671, 0.641, 0.630, and 0.502, respectively. The AUC of the combination of TC, FFAs, IL-6, and ApoA1 was 0.812, with a sensitivity, specificity, and Youden index of 78.8%,72.4%, and 0.512, respectively. The AUC of the combination of TC, FFAs, IL-6, and the ApoA1/ApoB ratio was 0.805, with a sensitivity, specificity, and Youden index of 73.8%,75.9%, and 0.497, respectively (Fig. 3A, Table 6).

Fig. 3
figure 3

ROC curve analysis for predicting osteoporosis or osteopenia in the lumbar spine. A All patients, (B) male patients, and (C) female patients

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Table 6 ROC curve analysis for predicting osteoporosis or osteopenia in the lumbar spine
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In male patients, the optimal cut-off values of TC, FFAs, and IL-6 for the prediction of lumbar spine OP or osteopenia were 5.785, 0.512, and 8.750, respectively. The AUC of TC for predicting lumbar spine OP or osteopenia was 0.667, and the AUCs of FFAs and IL-6 were 0.683 and 0.678, respectively. The AUC of the combination of TC, FFAs, and IL-6 was 0.811, with a sensitivity, specificity, and Youden index of 79.4%, 74.2%, and 0.536, respectively. The AUC of the combination of TC, FFAs, IL-6, and the ApoA1/ApoB ratio was 0.812, with a sensitivity, specificity, and Youden index of 79.4%, 74.2%, and 0.536, respectively (Fig. 3B, Table 6).

In female patients, the optimal cut-off values of TC, FFAs, IL-6, ApoA1, and the ApoA1/ApoB ratio for the prediction of lumbar spine OP or osteopenia were 6.025, 0.526, 7.450, 1.385, and 1.476, respectively. The AUC of TC for predicting lumbar spine OP or osteopenia was 0.620, and the AUCs of FFAs, IL-6, ApoA1, and the ApoA1/ApoB ratio were 0.665, 0.669, 0.579, and 0.519, respectively. The AUC of the combination of TC, FFAs, IL-6, and ApoA1 was 0.805, with a sensitivity, specificity, and Youden index of 73.8%, 74.0%, and 0.478, respectively. The AUC of the combination of TC, FFAs, IL-6, and the ApoA1/ApoB ratio was 0.792, with a sensitivity, specificity, and Youden index of 65.1%, 80.0%, and 0.451, respectively (Fig. 3C, Table 6).

In both all patients and females, Joint Indicators–1: the combination of TC, FFA, IL-6, and ApoA1, Joint Indicators–2: the combination of TC, FFA, IL-6, and the ApoA1/ApoB ratio, Joint Indicators–3: the combination of TC, FFA, IL-6, ApoA1, and the ApoA1/ApoB ratio. In males, Joint Indicators–1: the combination of TC, FFA, and IL-6, Joint Indicators–2: the combination of TC, FFA, IL-6, and the ApoA1/ApoB ratio.

Joint application of blood lipid metabolism markers and IL-6 for predicting the risk of OP or osteopenia in the hip

ROC curve analysis was employed to assess the diagnostic efficiencies of TC, FFAs, IL-6, ApoA1, and the ApoA1/ApoB ratio, and their combination on OP or osteopenia in the hip.

Among all patients, the optimal cut-off values of TC, FFAs, IL-6, ApoA1, and the ApoA1/ApoB ratio were 5.635, 0.514, 7.650, 1.345, and 1.214, respectively. The AUC of TC of the prediction of hip OP or osteopenia was 0.556, and the AUCs of FFAs, IL-6, ApoA1, and the ApoA1/ApoB ratio were 0.687, 0.699, 0.584, and 0.536, respectively. The AUC of the combination of TC, FFAs, IL-6, and ApoA1 was 0.795, with a sensitivity, specificity, and Youden index of 72.6%, 78.3%, and 0.509, respectively. The AUC of the combination of TC, FFAs, IL-6, and the ApoA1/ApoB ratio was 0.803, with a sensitivity, specificity, and Youden index of 77.4%, 71.1%, and 0.485, respectively (Fig. 4A, Table 7).

Fig. 4
figure 4

ROC curve analysis for predicting osteoporosis or osteopenia in the hip. A All patients, (B) male patients, and (C) female patients

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Table 7 ROC curve analysis for predicting osteoporosis or osteopenia in the hip
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In male patients, the optimal cut-off values of TC, FFAs, IL-6, and the ApoA1/ApoB ratio for the prediction of hip OP or osteopenia were 5.605, 0.474, 9.400, and 1.468, respectively. The AUC of TC for the prediction of hip OP or osteopenia was 0.556, and the AUCs of FFAs, IL-6, and the ApoA1/ApoB ratio were 0.651, 0.715, and 0.500, respectively. The AUC of the combination of TC, FFAs, and IL-6 was 0.775, with a sensitivity, specificity, and Youden index of 63.2%, 88.7%, and 0.519, respectively. The AUC of the combination of TC, FFAs, IL-6, and the ApoA1/ApoB ratio was 0.792, with a sensitivity, specificity, and Youden index of 68.4%, 82.3%, and 0.507, respectively (Fig. 4B, Table 7).

In female patients, the optimal cut-off values of TC, FFAs, IL-6, ApoA1, and the ApoA1/ApoB ratio for the prediction of hip OP or osteopenia were 5.645, 0.518, 6.250, 1.425, and 1.214, respectively. The AUC of TC for the prediction of hip OP or osteopenia was 0.535, and the AUCs of FFAs, IL-6, ApoA1, and the ApoA1/ApoB ratio were 0.701, 0.701, 0.572, and 0.532, respectively. The AUC of the combination of ApoA1, FFAs, and IL-6 was 0.801, with a sensitivity, specificity, and Youden index of 77.9%, 75.6%, and 0.535, respectively. The AUC of the combination of TC, FFAs, IL-6, and the ApoA1/ApoB ratio was 0.801, with a sensitivity, specificity, and Youden index of 76.7%, 71.1%, and 0.478, respectively. Additionally, the AUC of the combination of TC, FFAs, IL-6, ApoA1, and the ApoA1/ApoB ratio was 0.803, with a sensitivity of 76.7% and a slight increase in prediction efficiency (Fig. 4C, Table 7).

In all patients, Joint Indicators–1: the combination of TC, FFA, IL-6, and ApoA1, Joint Indicators–2: the combination of TC, FFA, IL-6, and the ApoA1/ApoB ratio, Joint Indicators–3: the combination of TC, FFA, IL-6, ApoA1, and the ApoA1/ApoB ratio. In females, Joint Indicators–1: the combination of FFA, IL-6, and ApoA1, Joint Indicators–2: the combination of TC, FFA, IL-6, and the ApoA1/ApoB ratio, Joint Indicators–3: the combination of TC, FFA, IL-6, ApoA1, and the ApoA1/ApoB ratio. In males, Joint Indicators–1: the combination of TC, FFA, and IL-6, Joint Indicators–2: the combination of TC, FFA, IL-6, and the ApoA1/ApoB ratio.

Joint application of blood lipid metabolism markers and IL-6 for predicting the risk of OP or osteopenia in the lumbar spine or hip.

Using ROC curve analysis, the diagnostic efficiencies of TC, FFAs, IL-6, ApoA1, and the ApoA1/ApoB ratio and their combination on OP or osteopenia in the lumbar spine or hip were assessed.

Among all patients, the optimal cut-off values of TC, FFAs, IL-6, ApoA1, and the ApoA1/ApoB ratio were 5.605, 0.527, 7.500, 1.205, and 1.978, respectively. The AUC of TC for the prediction of OP or osteopenia in the lumbar spine or hip was 0.634, and the AUCs of FFAs, IL-6, ApoA1, and the ApoA1/ApoB ratio were 0.713, 0.670, 0.628, and 0.516, respectively. The AUC of the combination of TC, FFAs, IL-6, and ApoA1 was 0.846, with a sensitivity, specificity, and Youden index of 69.8%, 86.2%, and 0.560, respectively. The AUC of the combination of TC, FFAs, IL-6, and the ApoA1/ApoB ratio was 0.842, with a sensitivity, specificity, and Youden index of 70.3%, 86.2%, and 0.565, respectively (Fig. 5A, Table 8).

Fig. 5
figure 5

ROC curve analysis for predicting osteoporosis or osteopenia in the lumbar spine or hip. A All patients, (B) male patients, and (C) female patients

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Table 8 ROC curve analysis for predicting osteoporosis or osteopenia in the lumbar spine or hip
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In male patients, the optimal cut-off values of TC, FFAs, IL-6, and the ApoA1/ApoB ratio for the prediction of OP or osteopenia in the lumbar spine or hip were 5.605, 0.474, 8.750, and 1.127, respectively. The AUC of TC for the prediction of OP or osteopenia in the lumbar spine or hip was 0.596, and the AUCs of FFAs, IL-6, and the ApoA1/ApoB ratio were 0.688, 0.739, and 0.539, respectively. The AUC of the combination of TC, FFAs, and IL-6 was 0.829, with a sensitivity, specificity, and Youden index of 62.0%, 94.0%, and 0.560, respectively. The AUC of the combination of TC, FFAs, IL-6, and the ApoA1/ApoB ratio was 0.838, with a sensitivity, specificity, and Youden index of 74.0%, 84.0%, and 0.580, respectively (Fig. 5B, Table 8).

In female patients, the optimal cut-off values of TC, FFAs, IL-6, ApoA1, and the ApoA1/ApoB ratio for the prediction of OP or osteopenia in the lumbar spine or hip were 5.645, 0.518, 7.450, 1.385, and 1.476, respectively. The AUC of TC for the prediction of OP or osteopenia in the lumbar spine or hip was 0.620, and the AUCs of FFAs, IL-6, ApoA1, and the AUC of ApoA1/ApoB ratio were 0.728, 0.653, 0.611, and 0.502, respectively. The AUC of the combination of TC, FFAs, IL-6, and ApoA1 was 0.841, with a sensitivity, specificity, and Youden index of 66.7%, 93.2%, and 0.599, respectively. The AUC of the combination of TC, FFAs, IL-6, and the ApoA1/ApoB ratio was 0.828, with a sensitivity, specificity, and Youden index of 75.8%, 79.5%, and 0.553, respectively (Fig. 5C, Table 8).

In both all patients and females, Joint Indicators–1: the combination of TC, FFA, IL-6, and ApoA1, Joint Indicators–2: the combination of TC, FFA, IL-6, and the ApoA1/ApoB ratio, Joint Indicators–3: the combination of TC, FFA, IL-6, ApoA1, and the ApoA1/ApoB ratio. In males, Joint Indicators–1: the combination of TC, FFA, and IL-6, Joint Indicators–2: the combination of TC, FFA, IL-6, and the ApoA1/ApoB ratio.

Discussion

In addition to the liver and heart, bones are among the most critical organs involved in lipid metabolism. Hyperlipidaemia results in an abnormal accumulation of lipids in the bone marrow, which induces inflammation and inhibits osteoblast differentiation and mineralization through various mechanisms, ultimately leading to bone loss and osteoporosis. Osteoblasts have a high capacity for lipoprotein uptake; however, excessive accumulation of lipid droplets can impair their functionality. ApoA1 and ApoB are critical proteins involved in lipid metabolism and important biomarkers for detecting hyperlipidaemia.

Autophagy is a fundamental process of cellular self-regulation that significantly influences osteoblast functionality and bone formation. The autophagy of lipid droplets is called lipophagy which degrades triglycerides (TG) and cholesterol (TC) in lipid droplets through an autophagy-lysosome system, inducing the release of FFAs. Lipophagy can be triggered by excessive accumulation of lipids such as TC and FFAs in osteoblasts and inhibits osteoblast differentiation, leading to imbalanced bone metabolism, loss of bone trabeculae, and thinning of the trabeculae and cortex, ultimately affecting bone microstructure and density and resulting in decreased bone mass and OP [18].

Almost none of the previously published studies investigated the combination of the blood lipid profile and IL-6 in predicting OP. The relationship between IL-6 and various lipid metabolism markers has not received much attention. This study assessed the impact of blood lipid profile and IL-6 on bone metabolism and BMD, aiming to identify risk factors for OP and explore the diagnostic value of their combined application in OP and osteopenia. This study revealed that the levels of blood lipids and IL-6, and age were negative indicators affecting BMD, especially in women. The decrease in BMD was due to an increased trabecular cavity in women's bones [19], especially in postmenopausal women, who lose more bone mass than men as oestrogen levels decline [20]. Another reason why women have lower BMD than men may be differences in blood lipid levels. This study revealed that TC, HDL-C, and ApoA1 levels were markedly higher in women than in men and these blood lipid metabolism markers were negatively correlated with BMD. These factors lead to significantly lower BMD in women than in men.

BTMs are sensitive blood indicators that can quickly reflect the overall bone condition and predict changes in BMD. Higher levels of β-CTx are accompanied by reduced BMD because they promote bone remodelling [21]. This study revealed that β-CTx exhibited a negative correlation with BMD, whereas 25(OH)D exhibited a positive correlation with BMD. Therefore, the decrease in BMD due to increased β-CTx levels and a decrease in vitamin D should be concerning, as it could lead to OP or osteopenia.

This study revealed a close correlation between blood lipid levels and bone metabolism indices, indicating that blood lipid levels could impact bone metabolism. Among all patients, β-CTx was positively correlated with FFAs and IL-6. OC exhibited a positive correlation with ApoA1 and negative correlations with FFAs and IL-6. Moreover, 25(OH)D was negatively correlated with IL-6, TC, ApoB, and LDL-C.

Further sex stratification analysis revealed that the correlations were different for male and female patients. OC was negatively correlated with FFAs and IL-6 in both male and female patients. β-CTx was positively correlated with FFAs and IL-6 only in male patients, and 25(OH)D was negatively correlated with IL-6, TC, ApoB, and LDL-C only in female patients. Some research has indicated that people with higher vitamin D typically have lower LDL-C [22]. Reduced 25(OH)D levels increase the risk of OP [23]. Therefore, if a patient has increased TC or LDL-C levels and vitamin D levels are deficient, vitamin D can be replenished to prevent the development of OP.

TC and its metabolites can harm osteoblasts. Excessive TC intake and storage in the body can lead to hypercholesterolemia, which damages tissues and organs and leads to many metabolic diseases [24]. A meta-analysis that included 10 articles on lipid profiles and postmenopausal OP revealed that postmenopausal OP patients tended to have increased TC levels [25]. One study revealed that elevated TC suggested lower BMD and was positively associated with OP in older women [26].

This research indicated that an increased TC level can increase the risk of OP. In the unadjusted model, TC was negatively associated with lumbar BMD in males, and no correlation between TC and BMD was detected in females. However, after adjustment for age, TC exhibited negative associations with both hip BMD and lumbar BMD in males and females.

In previous studies, whether HDL-C is a risk factor or a protective factor in OP has been controversial. A Mendelian randomized multiomics study revealed that elevated HDL-C was responsible for a decrease in BMD [27]. Another investigation detected no considerable difference between them [28]. Additionally, an inquiry involving 1,158 inpatients explored the link between lipid concentrations and OP, indicating that HDL-C is a protective factor against OP in males and females [13]. Conversely, another investigation revealed that elevated HDL-C levels could be associated with an increased risk of OP [29].

This study revealed that HDL-C exhibited a negative correlation with BMD among all patients, but no correlation was detected after further sex stratification. OP is a dynamic development process, that is often accompanied by an increase in proinflammatory factors in the later stage, and proinflammatory factors can inhibit the synthesis of ApoA1 in the liver, thus inhibiting the production of HDL [30]. The difference in the opinions concerning HDL-C may be due to different study groups of patients or different manifestations at various stages of disease development. The precise mechanisms behind these differences are not fully understood and deserve further research in the future.

A study from the NHANES revealed that LDL-C exhibited a negative correlation with lumbar BMD in the 30-49-year age group in subgroup analyses after adjustment for the confounding factor of age [31]. However, a meta-analysis including 12 studies on postmenopausal women revealed no significant difference between LDL-C and osteopenia [3].

This study revealed that, after adjustment for age, LDL-C was negatively correlated with hip BMD and lumbar BMD in males and was only negatively correlated with lumbar BMD in females. The findings demonstrated a significant relationship between LDL-C and BMD.

ApoA1 is a regulatory component of lipid metabolism. As the main apolipoprotein of HDL-C, ApoA1 has been shown to have various cardiovascular benefits. Studies have shown that ApoA1 plays significant functional roles in various biological processes, including regulating bone metabolic homeostasis, systemic inflammation, nitric oxide production, and oxidative stress [32]. Studies have also demonstrated that ApoA1 can predict the occurrence and development of OP [33]. Recent data from experimental mice have indicated that deficiency of ApoA1 can lead to changes in the population of bone cell precursors, influencing bone metabolism by reshaping the phenotypic and molecular characteristics of bone marrow adipocytes [34]. OC is a product accumulated by osteoblasts in the bone extracellular matrix, and OC levels in serum can reflect the activity of osteoblasts and bone formation rate. This research indicated that ApoA1 was positively correlated with OC in the overall population, which might suggest that serum ApoA1 levels could reflect the activity of osteoblasts and that ApoA1 might affect OP by regulating osteoblast activity.

This study revealed that ApoA1 was significantly elevated in the OP and osteopenia groups. There was no considerable association between ApoA1 and BMD in male patients. However, in female patients, ApoA1 was inversely associated with lumbar BMD, and after adjustment for age, ApoA1 also showed an inverse association with hip BMD. This study suggested that elevated ApoA1 was a risk factor for OP in females.

ApoB is the main Apo responsible for transporting LDL-C in the body and is a major component of atherogenic lipoproteins with two main subtypes: apolipoprotein B48 and apolipoprotein B100 [35]. A study from the NHANES revealed that the relationship between ApoB and BMD varied by bone site, with ApoB inversely associated with lumbar BMD and not significantly related to total femur BMD [36]. The potential mechanism explaining the link between ApoB and BMD is unknown. One possible explanation is that high ApoB levels may trigger an inflammatory response, which can negatively affect bone mass by altering the activation of osteoclasts [37].

This study revealed that ApoB was negatively correlated with 25(OH)D in females, which suggested that ApoB might affect OP by negatively regulating 25(OH)D.

This study revealed that ApoB was notably greater in the OP and osteopenia groups according to lumbar spine T scores; however, no significant difference was found when the patients were grouped according to hip T scores. Regardless of sex, ApoB was negatively associated with lumbar BMD, but no relationship was found with hip BMD. These results suggested that ApoB might be related to BMD at specific sites and the findings were consistent with the literature.

Shono N reported that ApoB levels were negatively correlated with the number of capillaries surrounding type IIx muscle fibres in males [38]. Multiple studies have suggested that the ApoB/ApoA1 ratio, unlike traditional lipid parameters, can predict sarcopenia in elderly individuals and accurately reflect the severity of acute coronary syndrome in patients [38]. OP and cardiovascular disease exhibit common risk factors such as smoking, age, menopause, and vitamin D deficiency [39]; therefore, it is speculated that ApoB levels and the ApoB/ApoA1 ratio can also affect the microcirculation blood supply to bones, leading to OP. This study revealed that the ApoA1/ApoB ratio was positively correlated with lumbar BMD in men, but negatively correlated with hip BMD in all patients.

FFAs, also known as non-esterified fatty acids, are decomposed by triglycerides and can directly participate in metabolism in the blood. Studies have shown that bone marrow fat exerts lipid toxicity in bone by secreting adipokines and FFAs [40]. Due to lipid metabolism imbalance, excessive FFAs can be produced, which signal through the TLR4 pathway to activate macrophages and cause systemic inflammation, ultimately leading to bone damage [41]. High levels of FFAs detected in the bone marrow of elderly OP patients are associated with decreased osteoblast production and increased osteoclast production. Moreover, FFAs induce apoptosis and dysfunctional autophagy in osteoblasts, consequently influencing their differentiation and function [40]. This study revealed that the OP and osteopenia groups had significantly higher FFA levels than the normal bone mass group, moreover, FFAs were negatively associated with hip BMD and lumbar BMD in patients regardless of sex. Therefore, an increased FFA level can increase the risk of OP.

Studies have shown that adipocytes within the bone marrow can produce various cytokines, such as IL-6, which can disrupt the balance between osteocytes and adipocytes [16], and IL-6 can interact with precursors of osteoclasts to stimulate osteoclast proliferation via the RANK–RANKL–OPG pathway [16]. It has been shown that osteoblasts from patients with rheumatoid arthritis secrete more IL-6 in response to FFA stimulation. Osteoblast mineralization activity is negatively correlated with FFA-induced IL-6 secretion [42]. Thus, FFAs may be novel molecular factors through which adipose tissue can cause damage to subchondral bone [42].

This study revealed that the IL-6 level was the lowest in the normal bone mass group, the second lowest in the osteopenia group, and the highest in the OP group; moreover, the IL-6 level was negatively correlated with BMD. Therefore, this study suggested that IL-6 was a crucial factor in OP caused by various lipid metabolism disorders.

This study also showed that IL-6 was positively correlated with FFAs and negatively correlated with TC, ApoA1, HDL-C, ApoB, and LDL-C. However, according to the lumbar spine T scores, IL-6, TC, ApoA1, HDL-C, ApoB, and LDL-C were higher in the OP group than in the normal bone mass group. This phenomenon can be explained by the interaction of dyslipidaemia metabolism with IL-6. Adipocyte accumulation can release FFAs, which induce the production of proinflammatory factors like IL-6 [43]. Moreover, proinflammatory factors can inhibit the production of ApoA1 particles in the liver, thereby inhibiting the production of HDL [30]. IL-6 can also promote the metabolism of LDL-C by increasing the expression of LDLR and SR-B1 on the liver cell surface [30], which reduces TC and LDL-C levels and increases FFA levels. Furthermore, excess FFAs drive the production of IL-6, creating a vicious cycle [44]. In conclusion, FFAs are important factors that can increase the level of IL-6, which can also release more FFAs by promoting the metabolism of cholesterol and triglycerides.

Moreover, TC and LDL-C increased significantly at the initial stage of osteopenia, but were no longer elevated at the OP stage; therefore, no significant difference was detected between the OP and osteopenia groups.

In summary, an abnormal increase in blood lipid levels induces the production of FFAs, FFAs promote the expression of IL-6, which in turn intensifies lipid metabolism disorders, leading to decreases in TC, HDL-C, and LDL-C and increases in FFAs, forming a vicious cycle and thus aggravating the development of OP. In this study, the correlations of TC, ApoA1, ApoB, FFAs, and IL-6 with bone metabolism indices were discovered, suggesting that blood lipid and IL-6 levels might affect bone metabolism and lead to the development of OP. The specific mechanism by which lipid metabolism and IL-6 affect BMD is not fully clear and needs to be further explored in the future.

By ROC curve analysis, this study revealed that the combination of TC, FFAs, and IL-6 with ApoA1 or the ApoA1/ApoB ratio to diagnose OP or osteopenia was significantly more effective than any individual indicator.

This study revealed that the combined application of TC, FFAs, IL-6, and the ApoA1/ApoB ratio could effectively predict OP or osteopenia in the lumbar spine and hip in males; in females, both the combined application of TC, FFAs, IL-6, and ApoA1 and the combined application of TC, FFAs, IL-6, and the ApoA1/ApoB ratio could effectively predict OP or osteopenia in the lumbar spine and hip; in all patients and in females, based on the AUC comparison, the prediction effect of the combination of TC, FFAs, IL-6, ApoA1, and the ApoA1/ApoB ratio was similar to that of the combination of TC, FFAs and IL-6 with ApoA1 or the ApoA1/ApoB ratio.

Therefore, these results indicate that the combined application of TC, FFAs, and IL-6 with ApoA1 or the ApoA1/ApoB ratio could effectively reflect the OP status of the patients and act as an early warning indicator of OP.

Strengths and limitations

Few studies have investigated the relationship of the blood lipid profile and IL-6 with BMD. Additionally, almost none of the previously published studies investigated the combination of the blood lipid profile and IL-6 in predicting OP or osteopenia. This study carried out a detailed sex stratification analysis, comprehensively analysed the intrinsic correlation of these indicators, and suggested that the combined application of TC, FFAs, and IL-6 with ApoA1 or ApoA1/ApoB ratio could better predict OP or osteopenia in patients.

There were several limitations in this study. First, the patients were from the orthopaedics department only, which likely led to sampling bias. In the future, multicentre and large-sample studies should be conducted to eliminate bias and obtain data that can better represent the general population. Secondly, due to limited time and funds, no relevant animal experiments have been conducted. The specific mechanisms underlying the association of blood lipid profile and IL-6 with BMD remain not entirely understood and require further research. Thirdly, the differences in the opinions concerning HDL-C in the literature may stem from variations in patient groups or different manifestations at various stages of disease development, but the precise mechanisms behind these differences remain incompletely understood and deserve further investigation.

Conclusions

In summary, this study revealed that abnormal levels of blood lipid metabolism markers such as TC, ApoA1, ApoB, and FFAs could affect bone metabolism, and an increase in FFAs could also cause an increase in IL-6 to worsen the loss of bone mass, leading to OP. Multiple linear regression analyses and AUC comparisons revealed that the combined application of TC, FFAs, and IL-6 with ApoA1 or the ApoA1/ApoB ratio could better predict OP or osteopenia in patients, and the diagnostic efficiency was significantly better than that of any single indicator. This study provides a new target for the diagnosis and treatment of OP. Patients with early-stage OP could be better screened by examining blood lipid and IL-6 levels. Therefore, clinicians should be mindful of the importance of blood lipids and IL-6 and take necessary precautions to manage their patients’ blood lipid and IL-6 levels to prevent the occurrence of OP.

Data availability

The datasets of this study are available from the corresponding author under reasonable requests.

Abbreviations

OP:

osteoporosis

BTMs:

bone turnover markers

BMD:

bone mineral density

TC:

total cholesterol

TG:

triglyceride

HDL-C:

high-density lipoprotein cholesterol

LDL-C:

low-density lipoprotein cholesterol

ApoA1:

apolipoprotein A1

ApoB:

apolipoprotein B

FFA:

free fatty acid

IL-6:

interleukin-6

β-CTx:

β-crosslaps peptide

P1NP:

N-terminal propeptide of type 1 procollagen

OC:

osteocalcin

25(OH)D:

25-hydroxyvitamin D

BMI :

body mass index

CI:

confidence interval

ROC:

receiver operating characteristic

AUC:

area under the curve

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Acknowledgements

We thank Kuanhao Jiang and Yexin Feng for their contributions to language editing.

Funding

This work was supported by the National Natural Science Foundation of China [No. 81873128] and the Zhejiang Province Traditional Chinese Medicine Science and Technology Project [No.2023ZL461].

Author information

Authors and Affiliations

  1. Department of Clinical Laboratory, The Second Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China

    Liping Fan, Chong Chen, Yongwei Zhang & Yeqing Yang

  2. The Second Clinical Medical College of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China

    Jiahao Chen

  3. Department of Orthopaedics, The Second Affiliated Hospital of Zhejiang Chinese Medical University, No. 318 Chaowang Road, Hangzhou, Zhejiang, 310005, China

    Zhe Chen

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  2. Jiahao Chen
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  3. Chong Chen
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  4. Yongwei Zhang
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  5. Yeqing Yang
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  6. Zhe Chen
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Contributions

Liping Fan performed the formal analysis and wrote the main manuscript. Jiahao Chen and Chong Chen handled visualization. Yongwei Zhang and Yeqing Yang provided methodology. Zhe Chen performed the formal analysis, conducted supervision, and edited the final manuscript. All authors reviewed the manuscript.

Corresponding author

Correspondence to Zhe Chen.

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Ethics approval and consent to participate

Ethical approval for this study was granted by the Ethics Committee of The Second Affiliated Hospital of Zhejiang Chinese Medicine University (Approval No. 2024-LW-012-01).

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The authors declare no competing interests.

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Fan, L., Chen, J., Chen, C. et al. The diagnostic value of the combined application of blood lipid metabolism markers and interleukin-6 in osteoporosis and osteopenia. Lipids Health Dis 24, 38 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12944-025-02456-2

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  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12944-025-02456-2

Keywords

Lipids in Health and Disease

ISSN: 1476-511X