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Journal of Orthopaedic Surgery and Research logoLink to Journal of Orthopaedic Surgery and Research
. 2025 Aug 7;20:737. doi: 10.1186/s13018-025-06153-9

Association between lncRNA H19 and osteoporosis in postmenopausal patients with type 2 diabetes mellitus

Teng Yang 1,#, Xiuli Feng 2,#, Na Wang 2, Tongyu Zhang 3, Zhichen Zheng 3, Guofeng Wang 2,3,✉
PMCID: PMC12330039  PMID: 40775721

Abstract

Background

This study aimed to assess the expression level of long non-coding RNA H19 (lncRNA H19) in peripheral blood mononuclear cells (PBMCs) of postmenopausal patients with type 2 diabetes mellitus (T2DM) with comorbid osteoporosis (T2DM-OP), and to evaluate its diagnostic value and its role in the pathogenesis of T2DM-OP.

Methods

A total of 150 postmenopausal patients with T2DM were recruited from the First People’s Hospital of Lianyungang City, China. Based on the bone mineral density (BMD) results measured by dual-energy X-ray absorptiometry (DXA), the patients were stratified into the T2DM-OP group (n = 108) and the T2DM group (n = 42). Clinical data and laboratory parameters were collected, and quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to quantitatively determine the expression of lncRNA H19 in PBMCs.

Results

When compared with the T2DM group, the expression level of lncRNA H19 in PBMCs of T2DM-OP patients was significantly lower (P < 0.001). The results of bivariate analysis revealed that lncRNA H19 was positively correlated with albumin (ALB, R = 0.311) and BMD (R = 0.696), while negatively correlated with age (R = -0.514), glycated hemoglobin A1c (HbA1c, R = -0.272), fasting blood glucose (FBG, R = -0.275), and transforming growth factor-β1 (TGF-β1, R = -0.392). All of these correlations were statistically significant (R < 0.001). Binary logistic regression analysis identified age, body mass index (BMI), HbA1c, TGF-β1, and lncRNA H19 as independent risk factors for T2DM-OP. Additionally, multiple linear regression analysis demonstrated that age, HbA1c, FBG, TGF-β1, and BMD were key determinants of the expression of lncRNA H19. Receiver operating characteristic (ROC) curve analysis indicated that lncRNA H19 had high diagnostic accuracy for postmenopausal T2DM-OP, with an area under the curve (AUC) of 0.833.

Conclusions

The expression level of lncRNA H19 in PBMCs of postmenopausal T2DM-OP patients was significantly reduced. This reduction could contribute to the pathogenesis of T2DM-OP through the regulation of modulating glucose metabolism and the lncRNA H19/TGF-β1 signaling pathway. Moreover, its expression level may serve as a highly promising non-invasive biomarker with high diagnostic accuracy for the early detection of postmenopausal T2DM-OP.

Trial registration

Retrospectively registered (ChiCTR2300074807).

Keywords: Type 2 diabetes mellitus, Osteoporosis, Postmenopausal, Peripheral blood mononuclear cells, LncRNA H19, TGF-β1

Introduction

Type 2 diabetes mellitus (T2DM) is a prevalent chronic disease associated with various complications. Its primary characteristics include hyperglycemia, relative insulin deficiency, or insulin resistance [1]. Osteoporosis (OP) is primarily characterized by reduced bone strength and an increased risk of fractures. Increased bone fragility is a typical feature of OP, whereas decreased bone mineral density (BMD) and damage to the bone microstructure are its primary pathological features [2–4]. Both environmental and genetic factors contribute to OP [5]. Type 2 diabetes mellitus with comorbid osteoporosis (T2DM-OP) is defined as a serious chronic skeletal complication in diabetic patients, resulting from chronic hyperglycemia, the accumulation of advanced glycation end products (AGEs), oxidative stress, and other pathological factors [6]. Postmenopausal women are predisposed to OP [4, 7]. In contrast, women with ovarian dysfunction and estrogen deficiency are more vulnerable to oxidative stress and metabolic disorders of AGEs following the onset of T2DM. This pathological cascade leads to an imbalanced state in which bone resorption exceeds bone formation, resulting in accelerated bone loss and reduced BMD, ultimately promoting the development of OP [8].

With the acceleration of population aging and the increasing prevalence of diabetes, the incidence of OP associated with T2DM is rising annually [9]. Approximately 50% of postmenopausal women globally are affected by OP [10]. Postmenopausal OP is a chronic, progressive disease with a high risk of pathological fractures. Osteoporotic fractures reduce the quality of life and are associated with a higher incidence, mortality, and a substantial economic burden [11]. This significantly impacts the health of postmenopausal women and poses a major public health challenge. Evidence indicates that approximately one-third to one-half of women over 50 years of age will sustain osteoporotic fractures [12, 13]. Osteoporotic vertebral fractures are difficult to detect, and their incidence is anticipated to rise annually, affecting numerous postmenopausal women [14]. Measurement of BMD via dual-energy X-ray absorptiometry (DXA) is currently the clinical gold standard for OP diagnosis [15]. Although this technique offers advantages such as high objectivity, sensitivity, reproducibility, and accurate quantification, its clinical application is restricted by complex operations and high costs. Owing to limited technological and medical resources in some Chinese hospitals, this technique cannot be widely implemented, leading to limited clinical utility. Therefore, there is an urgent requirement for novel non-invasive biomarkers capable of predicting the severity of disease progression.

Long non-coding RNAs (lncRNAs) are transcripts exceeding 200 nucleotides in length without protein-coding capacity. Previous research has demonstrated that the long non-coding RNA H19 (lncRNA H19)/transforming growth factor-β1 (TGF-β1) signaling pathway regulates bone metabolic processes [16]. LncRNA H19 can regulate osteoblast differentiation via the Wnt/β-Catenin signaling pathway, thereby promoting bone remodeling [17]. As a member of the TGF-β superfamily, TGF-β1 exhibits multifunctional characteristics that govern cell proliferation and differentiation. This cytokine is predominantly distributed in bone tissue and serves as a pivotal regulatory factor for bone turnover, which plays a critical role in the pathogenesis of OP [18].

Thus, is lncRNA H19 a crucial factor in the pathogenesis of postmenopausal T2DM-OP? Can its expression level serve as a clinical biomarker for early disease prognosis? In this study, we quantitatively determined the expression level of lncRNA H19 in peripheral blood mononuclear cells (PBMCs) of postmenopausal women with T2DM, including those with and without OP. Additionally, we assessed its correlation with clinical indicators. This study aims to clarify the diagnostic value and mechanistic role of lncRNA H19 dysregulation in postmenopausal T2DM-OP.

Materials and methods

Study population and design

In this study, 150 postmenopausal women with T2DM were enrolled from the Department of Endocrinology at the First People’s Hospital of Lianyungang City between May and October 2023. According to the diagnostic criteria of the American Diabetes Association [19], diabetes was defined as fasting blood glucose (FBG) ⩾ 7.0 mmol/L, glycated hemoglobin A1c (HbA1c) ⩾ 6.5%, or the glucose level in the oral glucose tolerance test (OGTT) 2 hours after glucose load ⩾ 11.1 mmol/L. BMD measurements of the femur (femoral neck and total hip) and lumbar spine (L1-L4) were obtained using DXA and were expressed in g/cm2. The T-value was recorded, which was defined as the standard deviation (SD) difference between the subject’s BMD and the sex-matched peak bone mass of a healthy young population. To ensure measurement consistency, all DXA scans were performed and calibrated by a certified technician using the same equipment throughout the study. Based on European guidance for the diagnosis and management of OP in postmenopausal women [20], OP was defined as the situation where the average BMD at any measurement location (lumbar spine L1-L4, femoral neck, or total hip) was at least 2.5 SD lower than the reference value of young people. Based on this criterion, 150 postmenopausal women with T2DM were stratified into the T2DM group (n = 42) and the T2DM-OP group (n = 108).

The exclusion criteria were as follows: (1) Type 1 diabetes mellitus (T1DM); (2) Acute or chronic infectious diseases; (3) Severe acute complications of diabetes (e.g., diabetic ketoacidosis); (4) Concurrent endocrine disorders that affect bone metabolism (e.g., hyperparathyroidism, hyperthyroidism, Cushing’s syndrome, or bone-related autoimmune diseases); (5) A history of OP and currently receiving pharmacotherapy; (6) Malignancies; (7) Recent (< 6 months) use of bone-modifying agents (e.g., vitamin D, calcium supplements, or corticosteroids); (8) Severe damage to the heart, kidneys, liver, or other organs; (9) Chronic nicotine and alcohol dependence for at least 5 years; (10) Prolonged bedridden status; (11) Surgical menopause (e.g., post-oophorectomy or hysterectomy).

Sample size justification

The sample size of this study was primarily determined based on clinical feasibility. According to the outpatient data of the Department of Endocrinology (2022–2023), there was an average of 30–40 eligible postmenopausal patients with T2DM per month. During the 6-month study period, 150 eligible patients were consecutively enrolled, covering over 80% of potential candidates to ensure sample representativeness.

To verify whether the sample size was sufficient to detect the observed differences, a post-hoc power analysis was performed using the Mann-Whitney test module in G*Power 3.1 software. Based on the effect size, sample size, and significance level (α = 0.05, two-tailed) of lncRNA H19 expression, the statistical power (1-β) exceeded 80%. This indicates that the current sample size was sufficient to reliably detect differential expression of lncRNA H19 between the two groups. For diagnostic performance analysis, the Obuchowski method [21] was employed to verify that a sample size of 150 patients could detect biomarkers with an area under the curve (AUC) of at least 0.8 in over 90% of cases, thereby ensuring the reliability of receiver operating characteristic (ROC) curve results.

Data collection

Clinical and anthropometric data, including age, duration of diabetes, weight, and height, were retrieved from medical records. The body mass index (BMI) was calculated as weight (in kilograms) divided by the square of height (in square meters) (kg/m2).

Specimen collection and biochemical analysis

All participants were required to fast for at least 8 h. In the early morning, 5 mL of peripheral venous blood was collected, centrifuged, and the serum was separated. The Beckman Coulter AU5800 analyzer (Beckman Coulter, Inc., Brea, CA, USA) was used to quantitatively detect the levels of serum albumin (ALB), uric acid (UA), triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), homocysteine (HCY), and FBG. High-performance liquid chromatography (HPLC; Beckman Coulter, Inc.) was used for the quantitative determination of HbA1c. A sandwich enzyme-linked immunosorbent assay (ELISA) kit (LiankeBio, Hangzhou, China; Cat# EK981-96) was used to measure the serum level of TGF-β1.

Quantification of LncRNA H19 expression in PBMCs

Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used for the quantitative detection of the expression level of lncRNA H19 in PBMCs. PBMCs were chosen instead of plasma for the quantitative analysis of lncRNA H19 for the following reasons: (1) PBMCs can provide cellular RNA with higher integrity, which is critical for detecting low-abundance lncRNAs; (2) As immune cells, PBMCs can directly reflect the inflammation and osteoimmune regulation related to the pathogenesis of T2DM-OP; (3) This method aligns with clinical feasibility in resource-limited settings.

In the early morning, 5 mL of peripheral venous blood was collected and placed in an ethylenediaminetetraacetic acid dipotassium (EDTA-K2) anticoagulant tube. PBMCs were separated using peripheral blood lymphocyte isolation solution. According to the manufacturer’s instructions, total RNA was extracted from the isolated PBMCs using Trizol reagent. The concentration and purity of RNA were assessed using the ultraviolet spectrophotometer. Subsequently, the total RNA was reverse-transcribed into complementary DNA (cDNA) using a reverse transcription kit. Finally, using the SYBR Green chemical method, qRT-PCR was performed on the ABI 7500 Real-Time PCR System (Applied Biosystems, USA) with cDNA as the template.

The amplification procedure was as follows: pre-denaturation at 95°C for 10 minutes; 40 cycles, including 5 seconds of denaturation at 95°C, 30 seconds of annealing at 60°C, and 60 seconds of extension at 72°C. The primer sequences were as follows: lncRNA H19 forward primer 5’-GCCTTCCTGAACACCTTAGGC-3’ and reverse primer 5’-GCAGCCATAGTGTGCCGACT-3’; glyceraldehyde-3-phosphate dehydrogenase (GAPDH) forward primer 5’-GAACGGGAAGCTCACTGG-3’, and reverse primer 5’-GCCTGCTTCACCACCTTCT-3’. Using GAPDH as the endogenous control, the relative expression level of lncRNA H19 in PBMCs was calculated using the 2−∆∆CT method. The primers and qRT-PCR-related kits for lncRNA H19 and the endogenous control gene GAPDH were purchased from LiankeBio (Hangzhou, China; lncRNA H19: Cat# R11061.5, GAPDH: Cat# R11088.4, qRT-PCR kit: Cat# R11088.4).

Statistical analysis

Statistical analysis was performed using SPSS v27.0 (IBM Corp., NY, USA). Figures were generated using GraphPad Prism 9.5 (GraphPad Software, CA, USA). The Shapiro-Wilk test was used to test the normality of all continuous variables. Data with a normal distribution were presented as mean ± SD and analyzed using the independent-sample t-test; data with a non-normal distribution were expressed as the median (interquartile range, IQR) and analyzed using the Mann-Whitney U test. Box plots were used to show the distribution of lncRNA H19. Spearman’s correlation analysis was used to evaluate the binary correlation between lncRNA H19 and other variables. Logistic regression analysis was used to determine the influencing factors for postmenopausal T2DM-OP. The ROC curve was constructed, and AUC was calculated to evaluate the diagnostic value of lncRNA H19 in postmenopausal T2DM-OP patients. Multiple linear regression analysis was used to determine the factors influencing the expression of lncRNA H19. All statistical tests were two-sided tests, and a P value < 0.05 was considered statistically significant.

Results

Baseline characteristics

When compared to the T2DM group, the T2DM-OP group exhibited significantly older age (P < 0.001), higher levels of HbA1c (P = 0.018), FBG (P = 0.019), and TGF-β1 (P < 0.001). Conversely, the T2DM-OP group showed lower values in BMI (P = 0.019), ALB (P < 0.001), and BMD (P < 0.001). There were no significant differences between the two groups in terms of diabetes duration, UA, lipid profiles, or HCY (P > 0.05, Table 1).

Table 1.

Baseline characteristics between the T2DM group and the T2DM-OP group

Variables T2DM group T2DM-OP group P value
N 42 108
Age (years) 55(55,65) 67(59,71) < 0.001
BMI (kg/m2) 27.42(25.39,31.60) 26.30(24.02,28.75) 0.019
Diabetes duration (years) 9.50(2.00,15.00) 10.00(3.50,16.50) 0.496
ALB (g/L) 39.95(38.50,40.80) 37.95(35.65,39.25) < 0.001
UA (µmol/L) 263.60(235.00,324.70) 253.60(205.05,294.81) 0.122
TC (mmol/L) 4.85(4.50,6.38) 4.60(4.06,5.64) 0.077
TG (mmol/L) 1.50(1.22,2.25) 1.46(1.16,2.06) 0.181
HDL-L (mmol/L) 1.13(1.09,1.55) 1.20(0.99,1.42) 0.228
LDL-L (mmol/L) 3.08(2.94,3.22) 2.96(2.66,3.24) 0.082
HCY (µmol/L) 11.55(10.20,12.70) 12.05(8.83,13.80) 0.462
HbA1c (%) 8.65(7.10,10.00) 9.45(7.95,11.50) 0.018
FBG (mmol/L) 8.13(7.01,8.49) 8.99 (6.23,10.30) 0.019
TGF-β1 (ng/ml) 112.75(99.41,122.80) 145.28(134.35,154.89) < 0.001
BMD (g/cm2) 0.99(0.93,1.02) 0.68(0.63,0.73) < 0.001
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Abbreviations: T2DM, type 2 diabetes mellitus; T2DM-OP, type 2 diabetes mellitus with comorbid osteoporosis; BMI, body mass index; ALB, albumin; UA, uric acid; TC, total cholesterol; TG, triglycerides; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; HCY, homocysteine; HbA1c, glycated hemoglobin A1c; FBG, fasting blood glucose; TGF-β1, transforming growth factor-β1; BMD, bone mineral density

Visualization of differential expression of lncRNA H19 via box plots

Box plot analysis (x-axis: study groups; y-axis: expression levels of lncRNA H19) revealed that, in comparison to the T2DM group, the expression level of lncRNA H19 in the T2DM-OP group was significantly lower (P < 0.0001; Fig. 1).

Fig. 1.

Fig. 1

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Differential expression of lncRNA H19 between the T2DM group and the T2DM-OP group visualized by box plots. Abbreviations: T2DM, type 2 diabetes mellitus; T2DM-OP, type 2 diabetes mellitus with comorbid osteoporosis; lncRNA H19, long non-coding RNA H19. Notes: The box represents the IQR (25th-75th percentiles) with a midline at the median. Whiskers extend to extreme values within 1.5×IQR. ****P < 0.0001

Bivariate correlations between lncRNA H19 expression and other variables

Bivariate correlation analysis revealed that lncRNA H19 expression was significantly positively correlated with ALB (R = 0.311, P < 0.001; Fig. 2(b)) and BMD (R = 0.696, P < 0.001; Fig. 2(e)). Conversely, it was significantly negatively correlated with age (R = -0.514, P < 0.001; Fig. 2(a)), HbA1c (R = -0.272, P < 0.001; Fig. 2(c)), FBG (R = -0.275, P < 0.001; Fig. 2(d)), and TGF-β1 (R = -0.392, P < 0.001; Fig. 2(f)).

Fig. 2.

Fig. 2

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Bivariate correlations between lncRNA H19 expression and other variables. Abbreviations: lncRNA H19, long non-coding RNA H19; ALB, albumin; HbA1c, glycated hemoglobin A1c; FBG, fasting blood glucose; BMD, bone mineral density; TGF-β1, transforming growth factor-β1

Logistic regression analysis of the influencing factors for postmenopausal T2DM-OP

After adjusting for covariates, age (odds ratios (OR) = 1.479, 95% confidence interval (CI): 1.088–2.011, P = 0.012), BMI (OR = 0.360, 95% CI: 0.167–0.779, P = 0.010), HbA1c (OR = 2.591, 95% CI: 1.245–5.390, P = 0.011), TGF-β1 (OR = 1.178, 95% CI: 1.057–1.312, P = 0.003), and lncRNA H19 (OR = 0.008, 95% CI: 0.000-0.415, P = 0.017) were identified as factors significantly associated with postmenopausal T2DM-OP (Table 2). Due to the lack of a significant correlation, ALB (OR = 1.510, 95% CI: 0.662–3.444, P = 0.328) and FBG (OR = 1.359, 95% CI: 0.591–3.126, P = 0.470) were excluded.

Table 2.

Logistic regression analysis of the influencing factors for postmenopausal T2DM-OP

Factors B SE Wald χ2 P value OR 95%CI for OR
Age 0.391 0.157 6.244 0.012 1.479 1.088–2.011
BMI -1.021 0.394 6.723 0.010 0.360 0.167–0.779
ALB 0.412 0.421 0.958 0.328 1.510 0.662–3.444
HbA1c 0.952 0.374 6.487 0.011 2.591 1.245–5.390
FBG 0.307 0.425 0.521 0.470 1.359 0.591–3.126
TGF-β1 0.164 0.055 8.839 0.003 1.178 1.057–1.312
LncRNA H19 -4.865 2.033 5.726 0.017 0.008 0.000-0.415
Constant -39.746 23.116 2.956 0.086 0.000
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Abbreviations: SE, standard error; OR, odds ratios; CI, confidence interval; BMI, body mass index; ALB, albumin; HbA1c, glycated hemoglobin A1c; FBG, fasting blood glucose; TGF-β1, transforming growth factor-β1; lncRNA H19, long non-coding RNA H19

ROC curve analysis: diagnostic performance of lncRNA H19 for T2DM-OP

ROC curve analysis demonstrated that AUC of lncRNA H19 for diagnosing T2DM-OP was 0.833 (95% CI: 0.748–0.919), with an optimal cutoff value of 0.88, a sensitivity of 71.4%, and specificity of 97.2%. These findings confirm its significant diagnostic value for postmenopausal T2DM-OP (Fig. 3).

Fig. 3.

Fig. 3

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ROC curve analysis: diagnostic performance of lncRNA H19 for T2DM-OP. Abbreviations: lncRNA H19, long non-coding RNA H19; AUC, area under the curve; CI, confidence interval; ROC, receiver operating characteristic

Multiple linear regression analysis of influencing factors for lncRNA H19

Multiple linear regression analysis was performed with lncRNA H19 as the dependent variable and age, BMI, ALB, HbA1c, FBG, TGF-β1, and BMD as independent variables (Table 3). The regression model fit well (F = 41.711, P < 0.001). The analysis results showed that age (P = 0.005), HbA1c (P = 0.010), FBG (P < 0.001), TGF-β1 (P = 0.032), and BMD (P < 0.001) were influencing factors for lncRNA H19 expression.

Table 3.

Multiple linear regression analysis of influencing factors for LncRNA H19

Factors B (unstandardized coefficient) SE Beta (standardized coefficient) t P value
Constant -0.564 0.566 -0.996 0.321
Age -0.011 0.004 -0.205 -2.855 0.005
BMI -0.001 0.007 -0.004 -0.073 0.942
ALB 0.008 0.009 0.053 0.889 0.375
HbA1c 0.036 0.014 0.175 2.622 0.010
FBG -0.050 0.011 -0.293 -4.378 < 0.001
TGF-β1 0.003 0.001 0.150 2.171 0.032
BMD 1.758 0.191 0.725 9.218 < 0.001
R2 0.673
F 41.711***
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Abbreviations: lncRNA H19, long non-coding RNA H19; SE, standard error; BMI, body mass index; ALB, albumin; HbA1c, glycated hemoglobin A1c; FBG, fasting blood glucose; TGF-β1, transforming growth factor-β1; BMD, bone mineral density. Notes: ***P < 0.001

Discussion

Postmenopausal T2DM-OP is defined as a condition characterized by increased bone fragility and decreased bone mass in the skeletal system of postmenopausal T2DM patients [22]. As age advances, islet dysfunction and estrogen depletion jointly elevate the risk of fractures in postmenopausal T2DM patients, significantly impacting their lifespan and quality of life [23]. This has imposed a substantial economic burden on patients’ families and healthcare systems and has emerged as an urgent public health concern that requires immediate attention in contemporary society. It is estimated that the global prevalence of diabetes mellitus among adults aged 20 to 79 years is 10.5%, and it is projected to rise to 12.2% by 2045 [24]. Epidemiological data in China indicates that the prevalence rate of OP among individuals over 65 years old is 32%, and both T1DM and T2DM can increase the susceptibility to fractures [25]. Therefore, it is especially necessary to actively manage diabetic OP in clinical practice. Currently, there is still a dearth of effective biomarkers for detecting diabetic OP and grading the severity of the disease. Although bone turnover markers are associated with BMD and fracture risk and can predict therapeutic responses and adverse events in postmenopausal OP [26, 27], their specific application value and effectiveness in postmenopausal T2DM-OP still require further validation. In this context, this study explores the role and clinical relevance of lncRNA H19 in the pathogenesis of postmenopausal T2DM-OP, offering important references for clinical diagnosis and treatment.

LncRNAs are transcripts exceeding 200 nucleotides in length without protein-coding capacity. They play a crucial role in gene expression regulation and cell physiology and are anticipated to become biomarkers for numerous diseases, including diabetes complications [28]. LncRNA H19 is located in the telomere region of human chromosome 11p15.5, with a transcript length of 2.3 kb. This imprinted gene is only expressed in maternally inherited alleles [29]. As a pivotal regulator of osteogenic differentiation, lncRNA H19 is involved in mediating bone regeneration and regulating skeletal metabolic pathways [30].

The precise coupling between osteoblastic bone formation and osteoclastic resorption serves as the foundation for maintaining skeletal homeostasis, and the imbalance of this coupling relationship represents the core pathophysiological mechanism of OP [31]. The results of this study demonstrated that, compared with the T2DM group, patients in the T2DM-OP group exhibited significantly older age, elevated levels of HbA1c, FBG, and TGF-β1, while BMI, ALB, BMD, and lncRNA H19 expression levels decreased. After adjusting for covariates such as age, BMI, ALB, FBG, HbA1c, TGF-β1, and lncRNA H19, age, BMI, HbA1c, TGF-β1, and lncRNA H19 remained influencing factors for postmenopausal T2DM-OP, aligning with previous research findings [32–38].

The incidence rate of OP exhibits a positive correlation with age. Fragility fractures are highly prevalent among the elderly population and are closely associated with age-related OP [39]. As age advances, the bone-forming ability of osteoblasts declines, while simultaneously, the resorptive function of osteoclasts is relatively enhanced, resulting in an imbalance in bone metabolism, where bone resorption surpasses bone formation. This imbalance leads to a net loss of bone mass and an increase in skeletal fragility [38]. The incidence of OP in postmenopausal women has increased significantly, characterized by a marked decrease in estrogen levels. Estrogen deficiency can accelerate bone resorption, leading to thinning or discontinuity of bone trabeculae, rendering postmenopausal women more prone to OP [8]. Furthermore, persistent calcium loss and alterations in immune cell function collectively heighten the risk of OP in postmenopausal women [40, 41].

BMI represents a significant risk factor for OP. Studies indicated that the BMI of postmenopausal women with T2DM-OP was low [32, 42]. A higher BMI elevates the mechanical loading on bone tissue, stimulates osteoblast activity more strongly, enhances BMD, and decelerates the progression of OP [43]. The Osteoporosis Self-assessment Tool for Asians (OSTA) calculates OP risk scores using the following formula: OSTA score = [body weight (kg) - age (years)] × 0.2, suggesting that weight gain aids in reducing the risk of age-related OP [44]. A recent cross-sectional study further validated the diagnostic value of weight, BMI, and age in screening for OP and proposed new cutoffs for identifying high-risk women (weight < 57.4 kg, BMI < 23.8 kg/m², and age ≥ 72 years) [45]. However, extant evidence indicates that both low and high BMI elevate OP risk [32, 33]. Unfortunately, due to the limited sample size, it is currently infeasible to conduct BMI subgroup analysis to determine the diagnostic cutoff point values for OP.

HbA1c can reflect the stability of a patient’s blood glucose level. Hyperglycemia can inhibit the differentiation of osteoblasts and facilitate osteoclastogenesis [46]. Additionally, factors such as heightened levels of oxidative stress, accumulation of AGEs, reduced levels of insulin-like growth factor-1 (IGF-1), hormonal imbalances, and immune dysfunction collectively constitute the pathophysiological mechanism of OP [34].

TGF-β1 synthesized by osteoblasts exerts a positive regulatory effect on osteoblasts and a bidirectional regulatory effect on osteoclasts [47–50]. As a pivotal factor in maintaining bone metabolic balance, TGF-β1 plays a key role in the proliferation and differentiation of osteoblasts [51]. Research has demonstrated that high concentrations of TGF-β1 can promote osteoclast apoptosis, whereas low concentrations of TGF-β1 induce osteoclast maturation [52]. Xiao et al. [35] reported that the level of TGF-β1 in the serum of patients with T2DM was notably higher than that of healthy individuals. Animal studies by Liu et al. [36] demonstrated that the level of TGF-β1 secreted by senescent cells in the callus of elderly mice increased, which inhibited fracture healing in these mice. This implies that elevated levels of TGF-β1 may foster the occurrence and development of OP.

Previous study by Liang et al. [37] demonstrated that lncRNA H19 can function as a microRNA (miRNA) sponge, reducing the expression levels of miR-141 and miR-22, upregulating runt-related transcription factor 2 (RUNX2), and activating the Wnt/β-catenin signaling pathway to facilitate osteoblast differentiation. However, the association between lncRNA H19 and TGF-β1 in postmenopausal women with T2DM-OP remains unclear. This study revealed that, when compared with the T2DM group, the expression level of lncRNA H19 in PBMCs of patients in the T2DM-OP group was significantly decreased, whereas the level of TGF-β1 was elevated. After adjusting for factors including age, BMI, HbA1c, TGF-β1, and lncRNA H19, lncRNA H19 and TGF-β1 remained significant influencing factors associated with postmenopausal T2DM-OP. This finding implies that lncRNA H19 and TGF-β1 may collaborate in the development of postmenopausal T2DM-OP. A reduction in lncRNA H19 levels, when accompanied by an increase in TGF-β1 levels, may indicate an elevated susceptibility to postmenopausal T2DM-OP.

Further analysis of the correlations among lncRNA H19, TGF-β1, and other clinical parameters in the T2DM group and the T2DM-OP group revealed that the expression level of lncRNA H19 was positively correlated with ALB and BMD, yet negatively correlated with age, HbA1c, FBG, and TGF-β1. Additionally, age, HbA1c, FBG, TGF-β1, and BMD have been recognized as significant factors influencing the expression of lncRNA H19. These findings imply that the downregulation of lncRNA H19 expression may contribute to the pathogenesis of postmenopausal T2DM-OP, potentially facilitating an elevation in TGF-β1 expression via the lncRNA H19/TGF-β1 pathway. Huang et al. [16] verified that the lncRNA H19/miR-675 axis regulated osteoblast differentiation via the TGF-β1/Smad3/histone deacetylase (HDAC) signaling pathway, suggesting its participation in bone metabolism. Furthermore, Cipriani et al. [34] demonstrated that insulin resistance upregulated the expression of factors related to the TGF-β pathway via chronic inflammation and hyperglycemia, consequently impairing bone microstructure and heightening the risk of fractures. In this study, significant associations among lncRNA H19, blood glucose indicators (HbA1c and FBG), TGF-β1, and BMD suggest that lncRNA H19 may be implicated in insulin resistance-related bone metabolism regulation; however, its specific mechanism requires further verification. Therefore, the preliminary results of this study indicate a potential association between lncRNA H19 and TGF-β1 in the pathogenesis of postmenopausal T2DM-OP. To clarify the causal relationship, future longitudinal studies are warranted for further validation.

Mounting evidence suggests that non-coding RNAs (ncRNAs) play a crucial role in musculoskeletal disorders. Recent research findings have particularly emphasized their regulatory potential in OP [53–58]. After analyzing 14 in vitro and in vivo studies, the Gargano team [57] discovered that small interfering RNAs (siRNAs) can specifically silence key genes related to bone metabolism, thereby restoring the dynamic balance between osteoblasts and osteoclasts. Subsequently, the team [58] reviewed 17 studies on circular RNAs (circRNAs) and confirmed that molecules such as circular Forkhead box protein P1 (circFOXP1) and hsa_circ_0006215 can promote the osteogenic differentiation of BMSCs by sponging miRNAs and upregulating RUNX2. These findings are consistent with the phenomenon we observed, where the expression of lncRNA H19 is reduced and the level of TGF-β1 is increased. This implies that different types of ncRNA molecules (siRNA, circRNA, and lncRNA) may play synergistic or antagonistic roles at different nodes of the same pathological network, thus providing a theoretical basis for the targeted combination therapy for postmenopausal T2DM-OP.

The study yielded several key findings. Firstly, we reported for the first time the association between lncRNA H19 levels and postmenopausal T2DM-OP. In comparison with the T2DM group, the expression of lncRNA H19 was significantly lower in the T2DM-OP group. Secondly, bivariate correlation analysis demonstrated that the expression of lncRNA H19 was positively correlated with ALB and BMD, and negatively correlated with age, HbA1c, FBG, and TGF-β1. Thirdly, logistic regression analysis identified age, BMI, HbA1c, TGF-β1, and lncRNA H19 as independent influencing factors for postmenopausal T2DM-OP. Finally, linear regression analysis revealed that age, HbA1c, FBG, TGF-β1, and BMD were independent determinants of the expression of lncRNA H19. Collectively, these results indicate that lncRNA H19 may participate in the pathogenesis of postmenopausal T2DM-OP through mechanisms related to glucose metabolism and the lncRNA H19/TGF-β1 signaling pathway. It is noteworthy that the ROC analysis in this study demonstrated that the AUC of lncRNA H19 in PBMCs for diagnosing postmenopausal T2DM-OP was 0.833, with a sensitivity of 71.4% and specificity of 97.2%, indicating its considerable diagnostic value. This finding suggests that lncRNA H19 may serve as a novel non-invasive biomarker for postmenopausal T2DM-OP.

However, this study has several limitations. Firstly, as a cross-sectional investigation, it is impossible to establish causal relationships. Further animal experiments and in vitro studies are warranted to validate the causal role of lncRNA H19 and its potential regulatory effect on TGF-β1 in the pathogenesis of postmenopausal T2DM-OP through the lncRNA H19/TGF-β1 signaling pathway. Secondly, the sample size was relatively limited and the data were non-normally distributed. This necessitates future studies to adopt previous non-parametric sample size estimation methods during the design phase and conduct large-scale multicenter cohorts to verify the clinical relevance, expression patterns, and mechanisms of action of lncRNA H19. Thirdly, the absence of a healthy control group and the failure to fully control confounding factors related to diabetes make it difficult to comprehensively explore the pathogenesis of T2DM-specific OP, which limits the analysis of dynamic changes of relevant parameters in the “healthy-T2DM-T2DM-OP” spectrum. Fourthly, the lack of measurement of insulin resistance indicators and inflammatory markers makes it impossible to directly elucidate the upstream role of insulin resistance in the lncRNA H19/TGF-β1 axis. Therefore, future research needs to supplement relevant data to improve understanding of its mechanism of action. It is important to note that subsequent studies will include healthy controls for triple comparisons to clarify the specific expression of lncRNA H19 and related indicators in the disease.

Conclusions

In conclusion, the expression of lncRNA H19 in PBMCs of postmenopausal T2DM-OP patients may contribute to the onset and progression of the disease via pathways related to glucose metabolism and transforming growth factors. Therefore, monitoring the changes in lncRNA H19 levels is highly valuable for the early prediction of postmenopausal T2DM-OP.

Acknowledgements

Not applicable.

Abbreviations

AGEs

Advanced glycation end products

ALB

Albumin

AUC

Area under the curve

BMD

Bone mineral density

BMI

Body mass index

BMSCs

Bone marrow mesenchymal stem cells

cDNA

Complementary DNA

CI

Confidence interval

circFOXP1

Circular Forkhead box protein P1

circRNAs

Circular RNAs

DM

Diabetes mellitus

DXA

Dual-energy x-ray absorptiometry

EDTA-K2

Ethylenediaminetetraacetic acid dipotassium

ELISA

Enzyme-linked immunosorbent assay

FBG

Fasting blood glucose

GAPDH

Glyceraldehyde-3-phosphate dehydrogenase

HbA1c

Glycated hemoglobin A1c

HCY

Homocysteine

HDAC

Histone deacetylase

HDL-C

High-density lipoprotein cholesterol

HPLC

High-performance liquid chromatography

IGF-1

Insulin-like growth factor-1

IQR

Interquartile range

LDL-C

Low-density lipoprotein cholesterol

lncRNAs

Long non-coding RNAs

lncRNA H19

Long non-coding RNA H19

miRNA

microRNA

ncRNAs

Non-coding RNAs

OGTT

Oral glucose tolerance test

OP

Osteoporosis

OR

Odds ratios

OSTA

Osteoporosis self-assessment tool for Asians

PBMCs

Peripheral blood mononuclear cells

qRT-PCR

Quantitative reverse transcription polymerase chain reaction

ROC

Receiver operating characteristic

RUNX2

Runt-related transcription factor 2

SD

Standard deviation

SE

Standard error

siRNAs

Small interfering RNAs

TC

Total cholesterol

T1DM

Type 1 diabetes mellitus

T2DM

Type 2 diabetes mellitus

T2DM-OP

Type 2 diabetes mellitus with comorbid osteoporosis

TG

Triglycerides

TGF-β1

Transforming growth factor-β1

UA

Uric acid

Author contributions

TY and XF were responsible for data curation, formal analysis, and original draft preparation. NW, TZ, and ZZ contributed to patient enrollment and data collection. GW oversaw project administration, manuscript review, and editing. All authors read and approved the final manuscript.

Funding

This study was funded by 2024 Healthcare Quality (Evidence-Based) Management Research Project (YLZLXZ24G069), 2024 Lianyungang Association for Science and Technology Soft Science Research Project (Lkxyb24160), 2023 Lianyungang Sixth Phase “521” Scientific Research Funding Project (LYG06521202372), 2022 Lianyungang Health and Medical Technology Project (202206) and 2021 Lianyungang Elderly health research project (L202105).

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

The study protocol was approved by the Ethics Committee of Lianyungang First People’s Hospital (KY-20210712001-01) and registered with the Chinese Clinical Trial Registry (ChiCTR2300074807). Written informed consent was obtained from all participants in accordance with the Declaration of Helsinki.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note

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

Teng Yang and Xiuli Feng contributed equally to this work.

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Associated Data

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Data Availability Statement

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

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