Functional mechanism and clinical implications of lncRNA NEAT1 in traumatic fractures and their correlation with delayed healing

Abstract

Background

The clinical diagnosis of delayed fracture healing currently lacks molecular markers that exhibit both high sensitivity and robust dynamic detection capabilities. To evaluate the value of lncRNA NEAT1 for diagnosing delayed fracture healing and its potential mechanism of action.

Methods

122 traumatic fractures patients were collected, including 61 normal fracture healing (NFH) patients and 61 delayed fracture healing (DFH) patients. LncRNA NEAT1 and miR-654-3p and osteoblast differentiation marker genes expression levels were examined using RT-qPCR. ROC curves and logistic analysis were used to assess lncRNA NEAT1 diagnostic value. CCK-8 method was used to detect the cell activity of osteogenic differentiated cells. Levels of apoptosis in osteogenic differentiated cells detected by flow cytometry. Relationship between lncRNA NEAT1 and miR-654-3p was detected by a dual luciferase reporter gene assay.

Results

The expression of lncRNA NEAT1 was upregulated in the serum of the DFH group. After osteoblast differentiation treatment, lncRNA NEAT1 level reduced while the level of miR-654-3p increased. A targeting relationship was found between lncRNA NEAT1 and miR-654-3p.and the expression levels were significantly negatively correlated. The lncRNA NEAT1 affected cell activity and apoptosis levels of osteogenic differentiated cells by regulating miR-654-3p.

Conclusions

lncRNA NEAT1 expression was up-regulated in DFH patient serum, and it has high diagnostic value for delayed fracture healing. lncRNA NEAT1 targeting miR-654-3p affected the activity and apoptosis of osteogenic differentiated cells.

Background

Fractures are more prevalent in children and the elderly, involving either complete or partial disruption of the bone structure’s continuity [1, 2]. With the aging of the global population and the rapid advancement of the transportation and construction industries, traumatic fractures have emerged as a significant global public health concern [3, 4]. According to statistical data, approximately 190 million fractures occur globally each year, with over 20% requiring surgical intervention [5]. The disability rate resulting from insufficient medical resources in developing countries is considerably higher compared to that in developed countries [6]. Epidemiological studies have demonstrated that the risk of fractures is elevated by 4.05-fold in young men, 2.82-fold in individuals who consume alcohol, and similarly in those experiencing insufficient sleep [7]. It is widely recognized that the majority of fractures heal successfully and progressively restore bone functionality following appropriate treatment [8, 9]. Unfortunately, certain fracture patients may encounter delayed healing or non-healing, which can significantly impact the healing process and overall recovery outcomes [10]. Recently, a variety of factors have been proven to affect the healing of fractures. For instance, calcitonin can promote the healing of fractures [11]. Jintiange has a promoting effect on the healing of osteoporotic fractures in aged rats [12]. Stress-induced hyperglycemia can affect the healing process of tibial fractures after surgery [13]. Intermittent pneumatic compression can shorten the healing time of fractures, increase the healing rate of fractures, and enhance functional recovery [14]. Low-intensity pulsed ultrasound has a bone-inducing effect, which can accelerate the healing process and enhance the bending strength of bones [15]. Delayed fracture healing (DFH) represents a challenging issue in orthopedic treatment, with an incidence rate of approximately 10% [16]. The impact on patients’ quality of life can be huge, and the financial strain it puts on them can be considerable [17]. The early diagnosis of DFH is great significance for improving the clinical treatment of patients. Currently, the diagnosis of DFH primarily relies on imaging examinations; therefore, identifying biomarkers capable of diagnosing DFH holds significant clinical and medical value.

Recent studies have shown that a variety of non-coding RNAs play crucial roles in musculoskeletal diseases. For example, microRNAs have shown great potential in the treatment of tendon injury and osteoarthritis [18, 19]. The small interfering RNAs plays a significant role in tendon homeostasis [20], rheumatoid arthritis [21]and osteoporosis [22]. Circular RNAs have also been reported to be applied in the treatment of osteoporosis [23]. MiR-1271-5p interacts with ZBTB7A to participate in the healing process of occipital bone fractures, and it may be a potential target for the treatment of occipital bone fractures [24]. Long noncoding RNA (lncRNA) represents a class of RNAs that exceed 200 base pairs in length and do not possess protein-coding capabilities [25]. lncRNA can function in two primary manners: directly modulating protein expression by promoting or sequestering gene activity, or indirectly regulating the expression of protein-coding genes via microRNA-mediated mechanisms [26]. Recently, the discovery of the non-coding RNA regulatory network has offered a novel perspective for elucidating the molecular mechanisms underlying fracture repair [27]. Notably, lncRNA has emerged as a pivotal target for modulating osteoblast function via competitive regulation of microRNA (miRNA) expression [10]. For example, LncRNA SNHG1 delays fracture healing by regulating miR-181a-5p/PTEN axis [28]. The processes of osteogenic differentiation of human bone marrow stem cells was promoted by LncMSTRG.11341.25, which targeting miR-939-5p/PAX8 axis [29]. LncRNA MALAT1 reinforced the osteogenic activity of bone marrow mesenchymal stem cells by regulating miR-214 and inhibiting its targeted degradation of Runx2, a key factor for osteogenic differentiation [30]. The lncRNA CASC11 affects the process of delayed fracture healing by acting as a sponge for miR-1271-5p [10]. LINC00339 targets miR-16-5p to regulate osteoblasts, thereby influencing the process of fracture healing [31]. However, the specific molecular mechanism of lncRNANEAT1 is rarely reported. Therefore, elucidating the precise molecular mechanism of lncRNA NEAT1 in delayed fracture healing holds significant implications.

In this study, lncRNA NEAT1 was the research focus. The study aimed to elucidate the underlying mechanism of its role in the DFH of traumatic fractures. Additionally, we aimed to find novel molecular markers for the early diagnosis of DFH and to further identify potential therapeutic targets.

Methods

Participants

A total of 61 DFH patients and 61 NFH patients admitted to Xingtai General Hospital of North China Medical Health Group from April 2024 to July 2024 were selected as the research objects. The patients with normal fracture healing and those with delayed fracture healing were randomly selected from all the fracture patients. First, all the fracture patients who were treated in our hospital during the period from April 2024 to July 2024 were grouped. Then, 61 cases were randomly selected from each group. Inclusion criteria were as follows: (a) patients with a history of trauma and radiographic confirmation of a fracture. (b) Patients and their families provided informed consent. (c) patients had complete clinical data. (d) This was the patient’s first fracture due to trauma. Exclusion criteria were as follows: (a) The patient had hepatic and renal dysfunction. (b) patients were diagnosed with tumor-related diseases. (c) The patient had an immune system disorder. (d) Pathological fractures may result from conditions such as bone tuberculosis, bone tumors, diabetes or severe osteoporosis, among others. (e) Patients have a history of using corticosteroids, among other things.

Follow-up

In the present study, we conducted a 3-month follow-up DFH was defined as no callus or a small amount of callus at the fracture site, obvious fracture line, or obvious gap on X-ray examination at 3 months after treatment [32]. Based on this criterion, we divided patients into delayed fracture healing (DFH) group (n = 61) and non-delayed fracture healing (NFH) group (n = 61).

Samples of serum

On the next day of enrollment, 5 mL fasting venous blood was collected from all patients. The collected venous blood was centrifuged for 10 min at 4 °C and 3000 r/min to collect the supernatant.

Cell culture and transfection

Treatment of osteogenic differentiation (OD) was a key step in this study. MC3T3-E1 (SUNNCELL, Wuhan, China) were cultured in EMEM (MEM + NEAA) medium. This medium contained 10% FBS and 1% penicillin or streptomycin. The cells were cultured at 37 °C, 5% CO₂ and 95% air humidity.

LncRNA NEAT1siRNA and lncRNA NEAT1pcDNA and miR-654-3p inhibitors and miR-654-3p mimics and the control for lncRNA NEAT1siRNA(si-NC) and pcDNA overexpression control vector (only vector), both purchased from INNOCARE. They were transfected into differentiated cells using Lipofectamine 3000 (ThermoFisher, USA).

Osteogenic differentiation induction

The osteoblast induction medium consists of 20 mM β-glycerophosphate, 100 mg/mL ascorbic acid, 10% fetal bovine serum and EMEM (MEM + NEAA) medium medium. Add MC3T3-E1 to the cell culture vessel and add 4 ml of complete medium. Replace the complete medium every 48 h. Then rinse the cells three times with phosphate-buffered saline (PBS), and then add 4 mL of osteogenic induction medium. Subsequently, the cells continue to be cultured in the incubator for 15 days to promote differentiation.

Cell viability assay

The trypsin was used to treat the transfected MC3T3-E1 cells. 100 µL of the cell suspension was seeded into a 96-well plate. In each well, the 10 µL of CCK-8 solution was added. Finally, the optical density values were determined at a 450 nm.

Cell apoptosis assay

Differentiated and transfected MC3T3-E1 cells were collected and then 100 µL of binding buffer was added. 5 µL of PI and Annexin V-fuorescein isothiocyanate were added to the cell suspension. The cells were incubated for 15 min. Finally, the apoptosis rate was determined by flow cytometry.

RT-qPCR

The TRIzol Kit (ThermoFisher, USA) was used to extracted total RNA in patient serum and MC3T3-E1 cells. The SuperScript IV (ThermoFisher, USA) was used to reverse the RNA transcribed into cDNA. LncRNA NEAT1, miR-654-3p and osteogenic differentiation related genes expression levels were tested using SYBR Premix Ex TaqTM II (Takara, Japan) and miRNA Universal SYBR qPCR Master Mix (Yeasen, Shanghai, China). The reference genes were GAPDH and U6. And gene amplification was performed base on the manufacturer’s procedure. The gene expression was calculated by the formula 2 ^−ΔΔCt. The PCR primers are shown in Table 1.

Table 1.

Primer sequences used for PCR

Gene	Primer Sequence
lncRNA NEAT1	Forward	5’-GGCCAGAGCTTTGTTGCTTC-3’
	Reverse	5’-GGTGCGGGCACTTACTTACT-3’
miR-654-3p	Forward	5’-TCGGCAGGUGGUGGGCCGCAG-3’
	Reverse	5’-CACTCAACTGGTGTCGTGGA-3’
ALP	Forward	5’-AGTCAGCTGAAGTCTGGGAG-3’
	Reverse	5’-CTGCTTCCGAGACAGAGAGG-3’
OCN	Forward	5’-GACTGTGACGAGTTGGCTGA-3’
	Reverse	5’-CTGGAGAGGAGCAGAACTGG-3’
Runx2	Forward	5’-CCATAACGGTCTTCACAAA-3’
	Reverse	5’-AATGCGCCCTAAATCAC-3’
U6	Forward	5’-CTCGCTTCGGCAGCACA-3’
	Reverse	5’-AACGCTTCACGAATTTGCGT-3’
GAPDH	Forward	5’-TCCGGCACTACCGAGTTATC-3’
	Reverse	5’-GATCCGGTGTAGCAGATCGC-3’

ALP: Alkaline Phosphatase; OCN: Osteocalcin; Runx2: Runt-related transcription factor 2

Chi-square test analysis

Collect the clinical data of patients with normal fracture healing and those with delayed fracture healing, and then classify these data. The chi-square test was conducted using SPSS 27.0 to analyze the relationship between the clinical data of the patients and the delayed fracture healing.

Logistic regression analysis

The mRNA expression levels of lncNEAT1 and the clinical data of the patients were classified, and then a binary logistic regression analysis was performed using SPSS 27.0 to evaluate the diagnostic value of lncNEAT1 for delayed fracture healing.

Luciferase reporter assay

The starBase database was used to predict the binding sites of lncRNA NEAT1 and miR-645-3p. Then the recombinant plasmids lncNEAT1-WT and lncNEAT1-MUT were constructed. The mixture of the above transfection vectors was transfected with Lipofectamine 3000. Forty-eight hours post-transfection, the luciferase activity was assessed utilizing the luciferase reporter assay system.

Statistical analysis

The data were expressed as (Mean ± SD). The statistical analyses of the study were conducted using SPSS 27.0 and GraphPad Prism 10.1.2 software. Student’s t-test was used to compare differences between two groups, while the Tukey test was employed for comparisons among multiple groups. Chi-square test was used to analyze the relationship between clinical characteristics and delayed fracture healing. Logistic regression analysis and Receiver Operating Characteristic Curve ‌(ROC) evaluated the diagnostic value of lncRNA NEAT1 for delayed fracture healing. p < 0.05 was considered statistically significant.

Results

Expression and clinical significance of lncRNA NEAT1

The study first analyzed the clinical data of the two groups of patients. There were no significant differences observed between the two groups in terms of age, gender, BMI, fracture severity, hypertension, or hyperlipidemia (Table 2). This result suggested a notable concordance and comparability between the two patient groups, as well as a high degree of reliability in the study design. Next, we analyzed the lncRNA NEAT1 expression levels in the serum of the two groups patients. The RT-qPCR results demonstrated that lncRNA NEAT1 expression level in the serum of the DFH group was elevated compared to NFH group (p < 0.001, Fig. 1A). The ROC curve analysis revealed that the sensitivity and specificity of lncRNA NEAT1 were 82% and 78.7%, respectively (p < 0.001, Fig. 1B). The AUC was 0.858, with a 95% confidence interval ranging from 0.791 to 0.921 (p < 0.001, Fig. 1B). In addition, binary logistic regression analysis revealed that lncRNA NEAT1 could a potential risk factor for delayed healing of traumatic fractures (Table 3). The abnormal elevation of lncRNA NEAT1 in the DFH group serum may be associated with DFH.

Table 2.

Basic data of patients

parameters	non-delayed healing (NDH; n = 61)	delayed healing (DH; n = 61)	p
Age			0.587
>50	31	28
≤ 50	30	33
Gender			0.716
Male	27	29
Female	34	32
BMI (kg/m2)			0.584
>23.9	36	33
≤ 23.9	25	28
Severity of fracture			0.364
Complete fracture	26	31
Incomplete fracture	35	30
hypertension			0.356
yes	27	22
no	34	39
hyperlipidemia			0.143
yes	30	22
no	31	39

BMI: Body Mass Index

Fig. 1.

Expression and clinical value of lncRNA NEAT1. (A) Expression of lncRNA NEAT1 in the serum of patients with normal fracture healing (NFH) and delayed fracture healing (DFH). (B) LncRNA NEAT1 diagnostic value in delayed fracture healing (AUC = 0.856, 95% CI: 0.791–0.921). ***p < 0.001

Table 3.

Logistic correlation analysis of the determinants for DFH

Parameters	OR	95% CI	p
lncRNA NEAT1	13.906	4.977–38.699	<0.001
Age	1.323	0.565–3.101	0.519
Gender	1.239	0.530–2.893	0.621
BMI	1.521	0.623–3.716	0.357
Severity of fracture	1.135	0.484–2.663	0.770
hypertension	1.174	0.482–2.864	0.724
hyperlipidemia	1.131	0.475–2.697	0.781

BMI: Body Mass Index

Alterations in the expression levels of osteoblast marker genes and the lncRNA NEAT1

To further study the potential mechanism of lncRNA NEAT1 in the DFH. We induced MC3T3-E1 osteoblast differentiation in vitro. It is well known that the successful induction of osteoblast differentiation is the most critical step in this experimental process. Consequently, to examine whether osteoblasts were differentiated, we assessed osteoblast differentiation marker genes expression levels using RT-qPCR. The results demonstrated that the Alkaline Phosphatase (ALP), Osteocalcin (OCN), and Runt-related transcription factor 2 (Runx2) expression levels in the osteoblast differentiation group (OD) were elevated (p < 0.001, Fig. 2A-C). In parallel, we examined the lncRNA NEAT1 expression level in induced differentiated MC3T3-E1 cells. The results demonstrated that the lncRNA NEAT1 expression level was reduced in the OD group (p < 0.001, Fig. 2D). These results showed that MC3T3-E1 osteoblasts were successfully induced and differentiated.

Fig. 2.

Alterations in the expression levels of osteoblast marker genes and the lncRNA NEAT1. Differentiation treatment increased mRNA expression levels of ALP (A), OCN (B) and ALP (C) in osteoblasts. (D) Differentiation treatment increased the expression level of lncRNA NEAT1 in osteoblasts. ***p < 0.001

Effect of lncRNA NEAT1 upregulation on osteoblasts

lncRNA NEAT1 siRNA and lncRNA NEAT1 pcDNA were transfected into MC3T3-E1 osteoblasts, and the lncRNA NEAT1 expression level was successfully inhibited and increased (p < 0.001, Fig. 3A). The CCK-8 assay results demonstrated that, in comparison to the OD + NC group, the lncRNA NEAT1 siRNA markedly enhanced the cell activity of MC3T3-E1 osteoblasts, whereas the lncRNA NEAT1 pcDNA substantially diminished their cellular activity (p < 0.001, Fig. 3B). On the contrary, the lncRNA NEAT1 siRNA markedly decreased the apoptosis rate of MC3T3-E1 osteoblasts, whereas the lncRNA NEAT1 pcDNA substantially elevated the apoptosis rate in comparison to the OD + NC group (p < 0.001, Fig. 3C). Next, we examined the expression levels of osteoblast differentiation marker genes in transfected MC3T3-E1 cells. The results showed that, compare with the OD + NC group, the lncRNA NEAT1 siRNA enhanced the expression levels of ALP, OCN, and Runx2, whereas the lncRNA NEAT1 pcDNA increased their expression levels (p < 0.001, Fig. 3D-F).

Fig. 3.

Effect of lncRNA NEAT1 upregulation on osteoblasts. (A) Effects of lncRNA NEAT1 siRNA and pcDNA on lncRNA NEAT1 expression levels (B) Effects of lncRNA NEAT1 siRNA and pcDNA on cell activity of differentiated osteoblasts. (C) Effects of lncRNA NEAT1 siRNA and pcDNA on apoptosis in differentiated osteoblast cells. Effects of lncRNA NEAT1 siRNA and pcDNA on differentiated osteoblast marker genes (D) ALP, (E) OCN and (F)Runx2. *** p < 0.001

lncRNA NEAT1 interacts with miR-654-3p to affect osteoblasts

We used the starBase database to predict the downstream targets of lncRNA NEAT1. We found that miR-654-3p was one of the better-targeted molecules. Additionally, there is a report in the literature indicating that miR-654-3p can affect the osteoblast activity and differentiation during delayed fracture healing. Therefore, we chose miR-654-3p as the research object for the downstream target of lncRNA NEAT1. We employed RT-qPCR to quantify the miR-654-3p expression of the two groups. The results demonstrated that the miR-654-3p serum expression of DFH patient group was reduced compared to NFH group (p < 0.001, Fig. 4A). Next, we validated the relationship between lncRNA NEAT1 and miR-654-3p through a dual-luciferase reporter gene assay. The results demonstrated that the miR-654-3p inhibitors markedly enhanced the luciferase activity of lncRNA NEAT1-WT, whereas the miR-654-3p mimics suppressed this activity (p < 0.001, Fig. 4B). Notably, neither lncRNA NEAT1 siRNA nor pcDNA had any effect on the luciferase activity of lncRNA NEAT1-MUT (p < 0.001, Fig. 4B). Meanwhile, the results of correlation analysis showed that there was a negative correlation between lncRNA NEAT1 and miR-654-3p with r = -0.5937, p<0.001 (Fig. 4C). To explore the negative regulatory effect of lncRNA NEAT1 on miR-654-3p, lncRNA NEAT1 pcDNA were co-transfected into MC3T3-E1 cells along with miR-654-3p mimics. Results revealed that the lncRNA NEAT1 pcDAN significantly down-regulated the expression level of miR-654-3p mRNA (p < 0.001, Fig. 4D). Interestingly, the miR-654-3p mimics reversed this effect in miR-654-3p mRNA expression (p < 0.001, Fig. 4D). Meanwhile, the CCK-8 assay results demonstrated that lncRNA NEAT1 pcDNA significantly suppressed the cell activity of differentiated osteoblasts. Interestingly, miR-654-3p attenuated this effect (p < 0.001, Fig. 4E). The results of the apoptosis assay demonstrated that lncRNA NEAT1 pcDNA significantly enhanced the apoptosis rate of differentiated osteoblasts. Notably, miR-654-3p counteracted this effect (p < 0.001, Fig. 4F).

Fig. 4.

lncRNA NEAT1 interacted with miR-654-3p to affect osteoblasts. (A) Expression of miR-654-3p in the serum of patients with non - delayed fracture healing (NFH) anddelayed fracture healing (DFH). (B) Dual luciferase reporter gene assay confirmed the relationship between lncRNA NEAT1 and miR-654-3p target recognition. (C) Correlation analysis revealed that lncRNA NEAT1 was negatively correlated with miR-654-3p (r = -0.5937, p < 0.001). (D) Effects of lncRNA NEAT1 pcDNA and miR-654-3p mimics on miR-654-3p expression levels. (E) Effects of lncRNA NEAT1 pcDNA and miR-654-3p mimics on cell activity of differentiated osteoblasts (F) Effects of lncRNA NEAT1 pcDNA and miR-654-3p mimics on apoptosis in differentiated osteoblast cells *** p < 0.001

Discussion

DFH is a prevalent complication in orthopedics, with its etiology encompassing local inadequate blood supply, inflammatory dysregulation, reduced osteoblast activity, and abnormal apoptosis [33]. Additionally, inadequate clinical care constitutes a significant factor contributing to delayed fracture healing. For example, fixation stability and activity management, inadequate nutritional support, and failure to prevent and control infection can directly delay the healing process. Currently, the clinical diagnosis of delayed fracture healing primarily relies on imaging examinations such as X-rays and CT scans, in conjunction with clinical symptoms [34]. The clinical diagnosis of delayed fracture healing currently lacks molecular markers that exhibit both high sensitivity and robust dynamic detection capabilities. As a pivotal molecule regulating gene expression, lncRNA has increasingly come to light in the context of bone diseases. Notably, the role of lncRNA NEAT1 in multiple diseases has garnered attention. However, its underlying mechanisms in bone metabolic diseases remain elusive.

Osteoblast differentiation is extremely important for fracture healing, and its efficiency directly influences the rate of callus formation, the quality of mineralization, and the ultimate mechanical properties [35, 36]. Therefore, the induction of osteoblast differentiation was a critical step in this study. ALP promotes callus formation and bone tissue repair by enhancing bone matrix mineralization and modulating calcium and phosphorus metabolism [37]. OCN plays a direct role in the process of bone matrix mineralization [38]. OCN expression peaked at the late stage of osteogenic differentiation [39]. Runx2 directly drives mesenchymal stem cells to differentiate into osteoblasts by activating the expression of osteogenesis-related genes [40]. In this study, we initially induced osteoblast differentiation and subsequently observed that the expression levels of ALP, OCN, and Runx2 in the OD group were elevated compared to the control group. This suggested that we have successfully induced osteoblast differentiation.

NEAT1 is a perinuclear lncRNA that plays a critical role through the formation of paraspeckles. Recent studies found that NEAT1 exerts a critical regulatory function in the development and progression of various diseases. It had been shown that LncRNA NEAT1 inhibits HCC cell senescence through KIF11-dependent CDKN2A [41]. Exercise inhibits endothelial cell apoptosis and atherosclerosis through downregulation of NEAT1 [42]. Neat1 reduced neuronal apoptosis after hypoxia and glucose deprivation [43]. We found that lncRNA NEAT1 expression was significantly upregulated in delayed fracture healing patient serum, suggesting that it could serve as a potential biomarker. Next, we analyzed the value of lncRNA NEAT1 as a biomarker for diagnosing DFH. ROC curve analysis suggested that AUC was 0.856 (95% CI: 0.791–0.921), indicating that the sensitivity and specificity of lncRNA NEAT1 were 82% and 78.7%, respectively. These data suggest that lncRNA NEAT1 has a high capacity to distinguish between normal and delayed fracture healing. Also, logistic regression analysis showed that lncRNA NEAT1 was a potential risk factor for delayed fracture healing. These results implied a potential link between dysregulated expression of lncRNA NEAT1 of fracture patients and delayed fracture healing. It is well known that fracture healing is a highly complex bone regeneration process that involves the coordinated actions of multiple cell types and molecular factors [44]. Our research revealed that the lncRNA NEAT1 expression level can affect the cellular activity, apoptosis, and the expression level of osteoblast differentiation marker genes in differentiated osteoblasts. As we know, lncRNAs competitively bind miRNAs through base complementary pairing, blocking their inhibitory effects on downstream target genes. A study shows that lncRNA CASC11 regulates the process of delayed fracture healing through sponging miR150-3p [10]. Another study showed that miR-654-3p affected osteoblast activity and differentiation in delayed fracture healing by targeting EMP1 [45]. We confirmed the interaction between lncRNA NEAT1 and miR-654-3p by dual luciferase reporter gene assay and correlation analysis. When NEAT1 expression was elevated, miR-654-3p activity was attenuated, leading to suppression of target gene expression, decreased osteoblast activity and increased apoptosis.

Conclusions

lncRNA NEAT1 could effectively distinguish NFH patients and DFH patients, and it could be used as a molecular marker for the diagnosis of delayed fracture healing. The lncRNA NEAT1 affected osteoblast function by regulating miR-654-3p, providing a novel molecular mechanism for DFH. However, the potential mechanism of action of lncRNA NEAT1 affecting DFH still needs to be further elucidated.

Although in vitro cell models have advantages such as strong controllability and low cost in mechanism research, they also have certain limitations. The two-dimensional in vitro culture environment cannot fully simulate the three-dimensional microenvironment within the body and the interaction between cells and the matrix. The isolated culture system is unable to reflect the overall regulatory mechanisms of the neural-endocrine-immune network. The metabolic activity of cells in vitro generally differs from that in vivo.

Abbreviations

DFH

Delayed fracture healing

lncRNA

Long noncoding RNA

miRNA

MicroRNA

OD

Osteogenic differentiation

Author contributions

Meng Han developed the original idea and the protocol, abstracted and analyzed data, wrote the manuscript, and is a guarantor. Hua Meng, Zhaoyu Chen, Shenyi Lu, Qianqian Cheng, Yanqi Shang and Hongqing Wang contributed to the development of the protocol, abstracted data, and prepared the manuscript.

Funding

No funding.

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

This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Xingtai General Hospital of North China Medical Health Group. Informed consent was obtained from all individual participants included in the study.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.