Circulating miRNA markers and detection kits for diagnostic evaluation of spatial bone loss

Abstract

The application discloses a circulating miRNA marker and a detection kit for space bone loss diagnosis and evaluation, and belongs to the field of biomedical and molecular diagnosis technologies. Through bed rest simulation weightlessness experiment and multi-level bioinformatics analysis, a combination of miR-30a-5p, miR-135b-5p and miR-181c-5p is screened and identified from 937 serum circulating miRNAs, and the AUCs are 0.86, 0.93 and 0.93 respectively. Based on this, a standardized RT-qPCR detection kit is developed, taking miR-25-3p as an internal reference and cel-miR-39 as an exogenous quality control, and only about 400 muL of peripheral blood is needed to complete the detection. It is verified that the marker combination is stably expressed under microgravity and is negatively correlated with bone formation. The application has the advantages of non-invasiveness, convenience, high sensitivity and high specificity, and is suitable for astronaut bone health monitoring in orbit and early diagnosis of osteoporosis on the ground.

Description

Technical Field

[0001] This invention relates to the fields of biotechnology and molecular diagnostics, specifically to a circulating miRNA biomarker and detection kit for the diagnostic assessment of spatial bone loss. Background Technology

[0002] Currently, clinical diagnostic methods for spatial bone loss and osteoporosis include: bone mineral density testing, detection of bone metabolism biochemical markers, miRNA marker detection, and DNA methylation marker prediction. Existing clinical diagnostic methods for spatial bone loss and osteoporosis have the following main drawbacks: First, bone mineral density (BMD) testing can only reflect changes in bone mass in the middle and late stages, and cannot provide early warning. This is because BMD testing is based on a physical measurement of bone mineral content, and significant changes can only be detected when bone loss reaches a certain level (usually >30%), leading to delays in the optimal intervention time.

[0003] Second, traditional bone metabolism biochemical markers are unstable and subject to many interfering factors. This is because markers such as CTXI and PINP are affected by various factors such as circadian rhythms, diet, and liver and kidney function, and have large biological variability, making it difficult to establish stable diagnostic thresholds.

[0004] Third, single miRNA biomarkers lack sufficient sensitivity and specificity for diagnosis. Single miRNA biomarkers cannot fully reflect the complex bone metabolism regulatory network, and are prone to false positive or false negative results. Furthermore, existing biomarkers have not been specifically validated in the weightless environment of space and cannot be directly applied to astronaut bone health monitoring.

[0005] Fourth, there is a lack of bone loss detection methods suitable for the unique environment of the space station. Existing detection methods all rely on large equipment or complex operating procedures, which cannot meet the space station's requirements for miniaturized, portable, and simplified detection equipment. Summary of the Invention

[0006] This invention addresses the shortcomings of existing technologies by providing a circulating miRNA biomarker and detection kit for the diagnostic assessment of bone loss in space. The biomarker is a combination of miR-30a-5p, miR-135b-5p, and miR-181c-5p, exhibiting high sensitivity and specificity. Based on this, a standardized detection procedure suitable for space stations has been established. Verified through ground-based simulated weightlessness experiments and actual space station flights, this biomarker combination can be used for early, non-invasive, auxiliary diagnosis of different stages of bone loss in space, providing reliable technical support for astronaut bone health monitoring in orbit.

[0007] Therefore, in a first aspect, the present invention provides a circulating miRNA biomarker for the diagnostic assessment of spatial bone loss, said biomarker including miR-30a-5p, miR-135b-5p and miR-181c-5p.

[0008] Furthermore, the AUC value of the combined detection of miR-30a-5p, miR-135b-5p and miR-181c-5p is greater than 0.8.

[0009] Furthermore, the marker also includes miR-499a-5p.

[0010] A second aspect of the invention provides the use of the above-described markers in the preparation of products for the diagnosis or assessment of spatial bone loss.

[0011] A third aspect of the present invention provides a detection kit for the diagnostic assessment of spatial bone loss, comprising: primers or probes for amplifying the cDNA of each miRNA in the above-mentioned markers, primers or probes for internal reference genes, primers or probes for exogenous quality control genes, reverse transcription reagents, PCR reaction solution, water, and buffer solution.

[0012] Furthermore, the upstream primer sequences of the primers used to amplify the cDNA of each miRNA in the markers are determined as follows: the accurate sequence of the corresponding miRNA is obtained from the miRbase database, and the U base in the sequence is replaced with T.

[0013] Furthermore, the internal reference gene is selected from at least one of miR-25-3p, miR-16-5p, and miR-451a.

[0014] Furthermore, the exogenous quality control gene is cel-miR-39 and / or Arabidopsis thaliana miR-159a.

[0015] Furthermore, the test sample for the test kit is serum, plasma, urine, or saliva.

[0016] Furthermore, when the test sample for the test kit is serum or plasma, the volume of peripheral blood sample used is 250 μL to 500 μL.

[0017] Compared with the prior art, the present invention has at least the following beneficial effects: First, by employing a 90-day long-term simulated weightlessness experiment combined with multi-level bioinformatics analysis (Mfuzz temporal clustering → differential expression screening → bone mineral density correlation analysis → Lasso regression → ROC validation), three biomarkers, miR-30a-5p, miR-135b-5p, and miR-181c-5p, were precisely screened from 937 circulating serum miRNAs. The AUC values ​​of this biomarker combination were all greater than 0.8 (up to 0.93). Therefore, the technical solution of this invention has extremely high diagnostic sensitivity and specificity, enabling early non-invasive diagnosis of osteoporosis at different stages of development, thus overcoming the limitation of bone mineral density testing, which can only reflect changes in bone mass in the middle and late stages.

[0018] Secondly, due to the adoption of a standardized detection process using miR-25-3p as an internal reference and cel-miR-39 as a quality control, and the multiple validations of miR-25-3p in the tail-hanging model, the macaque bedridden model, and the osteoporosis model, it has been proven that miR-25-3p maintains stable expression in different species and different pathological models. Therefore, the technical solution of this invention has the technical effects of good detection repeatability, accurate quantification, and reliable results, and is suitable for laboratory and clinical promotion.

[0019] Third, since serum / plasma samples are used as the test subjects, only 250μL~500μL of peripheral blood is required, and the detection method is conventional RT-qPCR. Therefore, the technical solution of this invention has the technical effects of low sample volume, simple operation, non-invasive and safe. It can be realized in orbit through portable nucleic acid detection equipment, which gets rid of the dependence of traditional bone density detection on large equipment and complex procedures. It is particularly suitable for monitoring the bone health of astronauts in orbit on the space station.

[0020] Fourth, by employing a dual verification system of ground-based tail-suspended animal models and space-based flight cell models, the diagnostic effectiveness of this biomarker combination was confirmed for the first time in a real space microgravity environment. Therefore, the technical solution of this invention has the advantages of strong applicability to the space environment and high reliability of diagnostic results.

[0021] Fifth, since the miR-30a-5p / FoxK1 / glycolysis axis, miR-135b-5p / Runx2 / Smad5 pathway and miR-181c-5p / Sirt1 regulatory mechanism are revealed, the technical solution of this invention not only provides biomarkers for diagnosis, but also provides new targets for intervention and treatment of spatial bone loss and ground osteoporosis, thus achieving a technical effect that combines diagnosis and treatment. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments recorded in the embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0023] Figure 1 This invention provides a temporal analysis of circulating miRNA expression in the serum of volunteers who underwent 90 days of bed rest. Mfuzz cluster analysis was used to analyze the change patterns of all miRNAs. Clusters 1, 2, 3, 5, 6, 9, and 10 showed upregulation at one or two time points during bed rest, followed by a decline. Cluster 4 exhibited a wave-like trend. Cluster 7 showed upregulation after bed rest, recovering at day R30. Cluster 8 showed downregulation starting 30 days after the onset of bed rest and continuing until day R30. Red, blue, and green represent the degree of matching between gene changes and the main changes in the clusters, with red, blue, and green representing high, medium, and low levels, respectively.

[0024] Figure 2 shows the differentially expressed circulating miRNA screening analysis at different time points during bed rest, provided in an embodiment of the present invention; wherein... Figure 2A Analysis of differentially expressed circulating miRNAs during 30 days of bed rest; Figure 2B Analysis of differentially expressed circulating miRNAs during 60 days of bed rest; Figure 2C Analysis of differentially expressed circulating miRNAs during 90 days of bed rest; Figure 2D Analysis of differentially expressed circulating miRNAs for recovery after 30 days of bed rest.

[0025] Figure 3 This invention provides a correlation analysis between differentially expressed miRNAs and bone mineral density; wherein, red indicates a positive correlation, blue indicates a negative correlation, and so on. p<0.05, p<0.01.

[0026] Figure 4 This invention provides a correlation analysis of differentially expressed miRNAs with bone metabolism biochemical indicators; wherein, A represents the correlation analysis between miRNAs and serum bone metabolism biochemical indicators; B represents the correlation analysis between miRNAs and urinary bone metabolism biochemical indicators; red indicates a positive correlation, blue indicates a negative correlation, and so on. p<0.05, p<0.01.

[0027] Figure 5This invention provides an intersection analysis of differentially expressed circulating miRNAs at different time points during bed rest; wherein, A is a Venn diagram of the intersection of differentially expressed miRNAs during bed rest from day P15 to day R30; and B is a heatmap of miRNA expression at more than two time points.

[0028] Figure 6 This invention provides a miRNA Lasso regression screening analysis in an embodiment of the invention; where A is the Lasso regression cross-validation curve; and B is the Lasso coefficient path diagram.

[0029] Figure 7 This invention provides a validation of differentially expressed circulating miRNA detection in an embodiment of the invention. The differentially expressed miRNAs in the serum of bedridden volunteers were detected, with miR-25-3p used as an internal reference gene for correction. The detection results are displayed as a scatter plot and represented as x ± SEM. : 0.01 <p<0.05; 0.001 <p<0.01; 0.0001 <p<0.001; p < 0.0001.

[0030] Figure 8 This is the second verification of differentially expressed circulating miRNA detection provided in the embodiments of the present invention; wherein, the differentially expressed miRNA in the serum of bedridden volunteers was detected, with miR-25-3p as an internal reference gene for correction, and the detection results are displayed as a scatter plot and expressed as x ± SEM; : 0.01 <p<0.05; 0.001 <p<0.01; 0.0001 <p<0.001; p < 0.0001.

[0031] Figure 9 ROC curve analysis of candidate miRNA biomarkers provided in this embodiment of the invention; wherein, ROC curve analysis of candidate serum miRNA biomarkers for weightlessness and bone loss, AUC = area under the curve, CI = confidence interval.

[0032] Figure 10ROC curve analysis of candidate miRNA biomarkers provided in this embodiment of the invention; wherein, ROC curve analysis of candidate serum miRNA biomarkers for weightlessness and bone loss, AUC = area under the curve, CI = confidence interval.

[0033] Figure 11 This invention relates to changes in the femoral bone microstructure in tail-suspended mouse models. A represents three-dimensional μCT images of the distal femur of control and tail-suspended mice; BH represents quantitative μCT analysis of changes in bone mineral density (BMD), bone volume fraction (BV / TV), trabecular number (Tb.N), trabecular thickness (Tb.Th), trabecular connectivity density (Conn-D), trabecular separation (Tb.Sp), and structural pattern index (SMI) after 28 days of tail suspension; IK represents three-point bending analysis of femoral biomechanics; L represents HE staining results; Ctrl: control group; HU: hind limb tail-suspended unloaded group. p<0.01, p < 0.0001, n = 6.

[0034] Figure 12 Serum miRNA detection and analysis of tail-suspended mouse model mice provided in this embodiment of the invention; wherein, Ctrl: control group, HU: hind limb tail-suspended unloaded group, p<0.05, p<0.01, n=6.

[0035] Figure 13 The analysis of miRNA detection in the supernatant of MG63 cell culture medium for spaceflight provided in this embodiment of the invention; wherein, Ctrl: control, cell treatments are Bmp2 added, Bmp2 added and Jasplakinolide added, simulating 1G gravity, simulating 1G gravity with Bmp2 added, simulating 1G gravity with Bmp2 added and Jasplakinolide added, n=1.

[0036] Figure 14 This is a differentially expressed miRNA-target gene regulatory network diagram provided in an embodiment of the present invention; wherein, red represents miRNA and blue represents target genes regulated by miRNA.

[0037] Figure 15 shows the GO analysis of differentially expressed miRNA regulatory target genes provided in this embodiment of the invention; the bubble chart shows the biological processes of the top 10 gene ontologies (GOs) enriched in the miRNA regulatory network. Figure 15A ), cellular components ( Figure 15B ) and molecular functional terms ( Figure 15C The change in bubble color from red to blue indicates that the p-value has increased.

[0038] Figure 16 This invention provides differentially expressed miRNA KEGG analysis; wherein, the bubble diagram shows the KEGG pathway enriched with target genes in the miRNA regulatory network; the bubble color changes from red to blue, indicating that the p-value increases from small to large.

[0039] Figure 17 To verify the target genes miR-135b-5p and miR-181c-5p provided in the embodiments of the present invention, the effects of transfecting miR-135b-5p and miR-181c-5p mimics and inhibitors on the expression of related target genes in MG63 cells were measured. The results are shown in a scatter plot and represented as x ± SEM. : 0.01 <p<0.05; 0.001 <p<0.01。

[0040] Figure 18 To verify the miR-30a-5p target gene provided in the embodiments of the present invention, the effects of transfecting miR-30a-5p mimics and inhibitors on the expression of related target genes in MG63 cells were detected, and the results are shown in a scatter plot and represented as x ± SEM. : 0.01 <p<0.05; 0.001 <p<0.01。

[0041] Figure 19 This invention provides an embodiment of the regulatory effect of FoxK1 on skeletal glycolysis; wherein, osteoblast glycolysis was detected by (A) glucose uptake analysis; (BC) intracellular and extracellular lactate levels analysis; (DE) ATP generation detection; (FI) Seahorse analysis of cellular glycolytic metabolic rate; J: Visualization of 2-NBDG uptake in the femur collected 45 minutes after injection, scale bar: 100 μm. Ctrl: control group, MG: cell rotation group, FoxK1^oc- / -^: osteoblast conditional FoxK1 gene knockout mice. p<0.05, p<0.01, p<0.01; n=4.

[0042] Figure 20The following are examples of the effects of FoxK1 gene knockout on bone provided in this invention: (A) Three-dimensional μCT images of the distal femur of trabecular bone in WT mice and osteoblast-conditional FoxK1 knockout mice; (BH) Quantitative μCT analysis of changes in bone mineral density (BMD), bone volume fraction (BV / TV), trabecular number (Tb.N), trabecular thickness (Tb.Th), trabecular connectivity density (Conn-D), trabecular separation (Tb.Sp), and structural pattern index (SMI) after tail hanging for 28 days; (IK) Three-point bending test analysis of femoral biomechanics; (L) QPCR detection results of bone formation-related gene expression; Ctrl: control group, FoxK1^oc- / -^: osteoblast-conditional FoxK1 knockout mice. p<0.05, p<0.01, p<0.01; n=6. Detailed Implementation

[0043] To better understand the above technical solutions, the technical solutions of the embodiments of this application will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments of this application and the specific features in the embodiments are detailed descriptions of the technical solutions of the embodiments of this application, rather than limitations on the technical solutions of this application. In the absence of conflict, the embodiments of this application and the technical features in the embodiments can be combined with each other.

[0044] In a first aspect, the present invention provides a circulating miRNA biomarker for the diagnostic assessment of spatial bone loss, which is a combination of miR-30a-5p, miR-135b-5p and miR-181c-5p, with AUC values ​​of 0.86, 0.93 and 0.93, respectively, exhibiting extremely high diagnostic sensitivity and specificity.

[0045] In some embodiments, a circulating miRNA biomarker for the diagnostic assessment of spatial bone loss is a combination of miR-30a-5p, miR-135b-5p, miR-181c-5p and miR-499a-5p; wherein miR-499a-5p (AUC=0.79) is used as an auxiliary biomarker, and the construction of a four-biomarker combined detection system can further improve the diagnostic coverage.

[0046] A second aspect of the present invention provides the use of the above-described biomarkers in the preparation of products for the diagnosis or assessment of spatial bone loss, particularly in the early non-invasive diagnosis or efficacy assessment of weightlessness-induced bone loss and the resulting osteoporosis.

[0047] A third aspect of the present invention provides a detection kit for the diagnostic assessment of spatial bone loss, comprising: primers or probes for amplifying the cDNA of each miRNA in the above-mentioned markers, primers or probes for internal reference genes, primers or probes for exogenous quality control genes, reverse transcription reagents, PCR reaction solution, water, and buffer solution.

[0048] Furthermore, the test samples for the test kit are serum, plasma, urine, or saliva.

[0049] Specifically, in addition to serum / plasma, urine or saliva can also be used as test samples. These samples also contain stable circulating miRNAs and are more non-invasive and convenient to collect, but the miRNA content is relatively low, requiring optimization of extraction and detection conditions. When the test kit uses serum or plasma as the test sample, the volume of peripheral blood sample used is 250μL~500μL.

[0050] In some embodiments, the upstream primer sequences of the primers used to amplify the cDNA of each miRNA in the markers are determined as follows: the accurate sequence of the corresponding miRNA is obtained from the miRbase database, and the U bases in the sequence are replaced with T. It is understood that, in addition to poly(A) tailing reverse transcription, stem-loop RT-PCR can also be used for miRNA reverse transcription. This method has a stronger specific recognition ability for miRNAs, but the operation is relatively complex.

[0051] In some embodiments, the internal reference gene is selected from at least one of miR-25-3p, miR-16-5p, and miR-451a; wherein, miR-25-3p is preferred. It is understood that, in addition to miR-25-3p, miR-16-5p or miR-451a may also be selected as internal reference genes. These miRNAs also have good stability in serum, but need to be validated for specific research models.

[0052] In some embodiments, the exogenous quality control gene is cel-miR-39 and / or Arabianipsis thalianami R-159a. It is understood that, in addition to cel-miR-39, other artificially synthesized miRNAs from other species (such as Arabianipsis thaliana miR-159a) may also be used as exogenous quality controls, as long as the miRNA is not endogenously expressed in the sample to be tested.

[0053] Example 1 I. Combination of Logos The biomarker combination consists of three circulating miRNAs in serum and / or plasma: (1) miR-30a-5p: significantly upregulated during bed rest at B30, B60 and B90 days, negatively correlated with tibial bone mineral density (r=-0.94), AUC=0.86; (2) miR-135b-5p: significantly upregulated during bed rest at B60, B90 and R30 days, and significantly negatively correlated with bone mineral density of the tibia and calcaneus (r=-0.94 and -0.98, AUC=0.93; (3) miR-181c-5p: significantly upregulated on days B30, B60 and B90 of bed rest, AUC=0.93.

[0054] The combined use of the above three miRNAs can improve diagnostic accuracy through joint detection, which is superior to the detection of a single biomarker.

[0055] II. Components of the Detection Kit The test kit includes the following components: (1) Specific primers or probes for miR-30a-5p, miR-135b-5p and miR-181c-5p; (2) Primers or probes for the internal reference gene miR-25-3p; (3) Exogenous primers or probes for controlling cel-miR-39 properties; (4) Reverse transcription reagents (including poly(A) polymerase, oligo-dT primers, reverse transcriptase, etc.); (5) PCR reaction solution (including SYBR Green PCR Master Mix, miScript Universal Primer, etc.); (6) RNase-free water and buffer solution.

[0056] The upstream primer sequence design method for miR-30a-5p, miR-135b-5p, and miR-181c-5p is as follows: The accurate sequence of the corresponding miRNA is obtained from the miRbase database (http: / / mirbase.org / ), and the U base is replaced with T to serve as the upstream primer. Specifically, the upstream primer sequence for hsa-miR-30a-5p is: TGTAAACATCCTCGACTGGAAG; the upstream primer sequence for hsa-miR-135b-5p is: TATGGCTTTTCATTCCTATGTGA; and the upstream primer sequence for hsa-miR-181c-5p is: AACATTCAACCTGTCGGTGAGT.

[0057] III. Detection Methods Includes the following steps: Step 1: Sample Collection and Processing Collect 5 mL of peripheral blood from the subject and place it vertically in a 4°C refrigerator for natural precipitation for 2 hours; centrifuge at 1900 rpm at 4°C for 10 minutes, and aspirate the supernatant serum / plasma into an RNase-free EP tube; centrifuge at 12000 rpm at 4°C for 10 minutes, and aspirate the supernatant into a new RNase-free EP tube, then freeze at -80°C. The required serum / plasma volume can be as low as 250 μL-500 μL.

[0058] Step 2: Total RNA extraction Total RNA was extracted using the miRNeasy Serum / Plasma Kit. Add 1 / 5 volume of QIAzol Lysis Reagent to the sample; add an equal volume of chloroform, vortex for 15 seconds, and incubate at room temperature for 2-3 minutes; centrifuge at 12000 rpm and 4°C for 15 minutes; extract the upper aqueous phase, add 1.5 volumes of 100% ethanol and mix well; transfer to an RNeasy MinElute centrifuge column, where total RNA binds to the membrane; elute with RNase-free water to obtain high-quality RNA.

[0059] Step 3: Add exogenous quality control During RNA extraction, 1.6 × 10⁻⁶ ppm was used. 8 The final concentration of copy number / μL was added to cel-miR-39 as an exogenous spike-in quality control to monitor RNA recovery rate and reverse conversion efficiency.

[0060] Step 4: Poly(A) tailing reverse transcription miRNA was reverse transcribed into cDNA using the poly(A) tailing method. The reaction system included: 10× miScript Nucleics Mix, 5× miScript HiSpec Buffer, miScript Reverse Transcriptase Mix, and RNA template. Reaction conditions: 37°C for 60 minutes, followed by 95°C for 5 minutes to inactivate the RNA. After the reaction, the cDNA was diluted to 100 μL with RNase-free water, and 2 μL was used for subsequent qPCR.

[0061] Step 5: Real-time quantitative PCR detection Configure the qPCR reaction system: 2×QuantiTect SYBR Green PCR Master Mix, 10×miScript Universal Primer, miRNA-specific upstream primer, and cDNA template. PCR program: 95°C pre-denaturation for 15 minutes; 94°C denaturation for 15 seconds, 55°C annealing for 30 seconds, 70°C extension for 30 seconds, for a total of 40 cycles.

[0062] Step 6: Data Analysis and Result Interpretation miR-25-3p was used as an internal reference gene for normalization correction, and cel-miR-39 was used as the quality control standard. The relative expression levels of each marker were calculated (2^-ΔΔCt method). When the expression levels of any two or more of miR-30a-5p, miR-135b-5p, and miR-181c-5p were simultaneously significantly upregulated, it was considered a positive case of spatial bone loss.

[0063] IV. Results Analysis Figure 1 High-throughput sequencing was used to detect the miRNA expression profiles of serum samples at different time points during the bed rest experiment (pre-flight P, during bed rest B, and post-return R). After quality control and normalization, soft clustering analysis was performed on the normalized expression matrix using the Mfuzz package in R. The fuzzy C-means algorithm was run, with the number of clusters set to c = 10, to calculate the membership degree of each miRNA to each cluster. All miRNAs were divided into 10 expression pattern clusters (Cluster 1-10), and time-series expression trend plots were drawn using the median of each cluster.

[0064] Mfuzz soft clustering analysis divided all detected miRNAs into 10 different temporal expression patterns ( Figure 1This study revealed the dynamic regulatory characteristics of miRNAs throughout the entire period of simulated weightlessness during bed rest. Seven gene clusters (Clusters 1, 2, 3, 5, 6, 9, and 10) exhibited similar temporal response patterns: expression was upregulated at one or two time points during bed rest, subsequently returning to baseline levels. This suggests that these miRNAs are primarily involved in acute stress responses and early adaptive regulation, being rapidly activated in the initial stages of simulated weightlessness to cope with environmental changes, and then declining as the body gradually adapts. Cluster 4, however, displayed a unique wave-like trend, with its expression levels fluctuating repeatedly during bed rest. This suggests that the miRNAs in this cluster may be related to periodic physiological rhythm regulation or feedback loops, reflecting the oscillating adjustment process of homeostasis during bed rest. In contrast, Cluster 7 showed relatively stable expression during bed rest, but significantly upregulated 30 days after recovery (R30), indicating that these miRNAs may primarily participate in readaptation and repair processes, playing a crucial role in the body's recovery from simulated weightlessness to normal gravity. Furthermore, the expression of Cluster 8 genes was downregulated from day 30 of bed rest (B30) and persisted until day 30 after recovery (R30), suggesting that the miRNAs in this cluster were persistently suppressed under prolonged simulated weightlessness exposure, and that this suppression was delayed, failing to return to normal levels even after recovery. This may be related to chronic adaptive changes or damage caused by bed rest. In summary, the above 10 expression patterns depict the phased functional division of miRNAs throughout the entire bed rest period. The temporal characteristics of different clusters provide important clues for further analysis of the regulatory network of miRNAs under simulated weightlessness conditions and for screening potential biomarkers.

[0065] Figure 2 shows the circulating miRNAs that can serve as biomarkers for monitoring and assessing weightlessness and bone loss. We analyzed the differentially expressed circulating miRNAs at each time point compared to the pre-bed rest period (P15 days). Using the pre-bed rest period (P15 days) as a baseline control, pairwise comparisons were performed with four time points: B30, B60, B90, and R30. Differential expression analysis was performed using the R language package DESeq2 (default parameters), with a screening threshold set to |log2FoldChange|>0.5 and P<0.05. For the differentially expressed miRNAs obtained, a volcano plot was generated to show the overall distribution characteristics, a heatmap was generated to show the expression patterns of differentially expressed miRNAs in each sample, and bar charts were generated to count the number of upregulated and downregulated miRNAs.

[0066] On day B30, 10 upregulated miRNAs and 14 downregulated miRNAs were obtained. Figure 2A ); on day B60, 8 upregulated miRNAs and 13 downregulated miRNAs were obtained. Figure 2B ); 13 upregulated miRNAs and 11 downregulated miRNAs were obtained on day B90. Figure 2C ); and after 30 days of recovery following bed rest, 13 upregulated miRNAs and 7 downregulated miRNAs were observed. Figure 2D These differentially expressed miRNAs serve as candidate genes for subsequent biomarker screening.

[0067] Figure 3 The normalized expression levels of candidate circulating miRNAs obtained from the aforementioned differential expression screening were correlated with bone mineral density (BMD) in the hip, femoral neck, tibia, and calcaneus of the subjects. Spearman's correlation test was performed using SPSS 26.0 to calculate the correlation coefficient (r) and corresponding P-value, with a significance threshold set at P < 0.05. Heatmaps were used to illustrate the relationship between miRNA expression levels and BMD.

[0068] The results are as follows Figure 3 As shown, two serum circulating miRNAs were found to have a significant negative correlation with the bone mineral density (BMD) of the subjects, suggesting that these miRNAs may serve as potential regulators or monitoring markers of weightlessness-induced bone loss. Specifically, the expression level of hsa-miR-135b-5p was significantly negatively correlated with both tibial BMD (Tibia Tt.vBMD) and calcaneal BMD (Calcaneus Tt.vBMD), with correlation coefficients of r = -0.94 (P<0.05) and r = -0.98 (P<0.01), respectively. The correlation with calcaneal BMD was particularly strong, approaching a completely negative correlation. Furthermore, the expression level of hsa-miR-1260b was significantly negatively correlated with calcaneal BMD, with a correlation coefficient of r = -0.91 (P<0.05). The above results indicate that as the expression levels of these two miRNAs in circulation increased, the bone mineral density of the weight-bearing bones (tibia and calcaneus) of the lower limbs of the subjects showed a significant decreasing trend. This suggests that hsa-miR-135b-5p and hsa-miR-1260b may participate in the bone loss process under simulated weightlessness conditions by regulating bone metabolism-related target genes, and have potential value as biomarkers for monitoring and assessing weightlessness bone loss.

[0069] Figure 4 The normalized expression levels of differentially expressed circulating miRNAs obtained from the aforementioned screening were paired with serum and urinary bone metabolism biochemical indicators at each time point for correlation analysis. Spearman's correlation test was performed using SPSS 26.0 to calculate the correlation coefficient r and corresponding P-value, with a significance threshold set at P < 0.05. A heatmap was used to illustrate the association strength and direction between each miRNA and bone metabolism indicators, with significance levels marked on the graph. P<0.05, P<0.01).

[0070] The results are as follows Figure 4 As shown, 16 serum circulating miRNAs were found to be significantly correlated with serum bone metabolism biochemical indicators, and 12 serum circulating miRNAs were significantly correlated with urinary bone metabolism biochemical indicators. These differentially expressed circulating miRNAs are closely functionally associated with bone metabolism processes. Serum bone metabolism indicators mainly reflect the systemic bone turnover status. The significant correlation between the 16 miRNAs and serum indicators (such as bone formation markers PINP and OCN, and bone resorption markers CTX-I and TRACP-5b) suggests that these miRNAs may participate in bone metabolic remodeling under simulated weightlessness conditions by regulating osteoblast differentiation, osteoclast activation, or calcium and phosphorus metabolism balance. The significant correlation between the 12 miRNAs and urinary bone metabolism indicators (such as urinary calcium, urinary CTX-I, and DPD) further suggests that changes in the expression of these miRNAs can reflect the pathological state of enhanced bone resorption and aggravated calcium loss, consistent with the trend of increased excretion of bone resorption end products in urine.

[0071] Based on the combined correlation results from serum and urine, these circulating miRNAs may act as key nodes in the bone metabolism regulatory network, playing an important role in simulated weightlessness-induced bone loss. This, combined with previous correlation analyses with bone mineral density (…), suggests… Figure 3 This study constructed a chain of evidence linking bone mineral density phenotype, bone metabolism biochemistry, and circulating miRNA regulation. This further supports the potential application value of these differentially expressed miRNAs as biomarkers for monitoring and assessing weightless bone loss, and provides important clues for subsequent research on target gene function verification and regulatory mechanisms.

[0072] Figure 5Using online Venn analysis software, to further focus on candidate biomarkers with sustained regulatory significance from differentially expressed miRNAs at various time points, this study collected the intersections of differentially expressed miRNAs at four time points (B30, B60, B90, and R30) compared to the pre-bed rest baseline (P15). Multiple Venn diagrams of these intersections were plotted to visually display the common and unique members of the differentially expressed miRNAs at each time point. After screening, 14 circulating miRNAs that showed sustained differential expression at multiple time points were identified. Compared with day 15, hsa-miR-590-3p, hsa-miR-1303, and hsa-miR-660-5p showed significant differences in expression at B30, B60, B90, and R30; hsa-miR-339-3p showed significant differences in expression at B60, B90, and R30; hsa-miR-17-5p showed significant differences in expression at both B30 and B60 time points; and hsa-miR-379-5p and hsa-miR-30a-5p showed significant differences in expression at both B30 and B90 time points. The following miRs showed significant differences in expression at time points B60 and B90: hsa-miR-499a-5p, hsa-miR-1275, hsa-miR-181c-5p, and hsa-miR-135b-5p; novel-hsa-miR26-5p showed significant differences at time points B30 and R30; hsa-miR-1307-3p showed significant differences at time points B60 and R30; and hsa-miR-328-3p showed significant differences at time points B90 and R30. See details. Figure 5 .

[0073] Figure 6 Lasso penalized regression analysis was employed, using the standardized expression levels of 14 differentially expressed circulating miRNAs obtained from the aforementioned multi-timepoint intersection screening as independent variables, and bone mineral density (Hip BMD, Neck BMD, TibiaTt.vBMD, Calcaneus Tt.vBMD) or comprehensive scores of bone metabolism biochemical indicators at various sites as dependent variables. A Lasso (Least Absolute Shrinkage and Selection Operator) regression model was constructed using the R language's glmnet package. The optimal regularization parameter λ (lambda.min) was determined through 10-fold cross-validation; miRNAs with non-zero coefficients at this λ value were retained as potential predictive biomarkers.

[0074] The results are as follows Figure 6As shown, seven miRNAs were identified as predictive biomarkers for simulated weightlessness and bone loss after screening: hsa-miR-590-3p, hsa-miR-660-5p, hsa-miR-135b-5p, hsa-miR-499a-5p, hsa-miR-30a-5p, hsa-miR-17-5p, and hsa-miR-181c-5p. The intersection of the miRNAs screened by correlation analysis and those screened by the Lasso regression model yielded five more miRNAs: hsa-miR-135b-5p, hsa-miR-590-3p, hsa-miR-499a-5p, hsa-miR-30a-5p, and hsa-miR-181c-5p. These five miRNAs were selected as candidate biomarkers for further screening.

[0075] Figure 7 qRT-PCR was used for validation: To independently validate the expression levels of differentially expressed miRNAs obtained from multi-timepoint intersection screening, real-time quantitative PCR (qRT-PCR) was mainly used to detect expression in serum samples at various time points (P15, B30, B60, B90, R30) during the bed rest experiment. Total RNA was extracted from serum using the TRIzol method, and cDNA was synthesized via reverse transcription. Then, miRNA qPCR amplification was performed using specific stem-loop primers. The previously screened and validated miR-25-3p was used as an internal control gene for expression normalization (this internal control showed stable expression levels in both weightlessness-induced bone loss and ground-borne osteoporosis). The relative expression level of each miRNA relative to the P15 baseline was calculated using the 2^(-ΔΔCt) method.

[0076] Statistical analysis: Compared with the P15 baseline, the significance of miRNA expression changes at each time point was assessed using one-way ANOVA combined with Dunnett's multiple comparisons, with a significance threshold set at P<0.05. GraphPad Prism was used to plot relative expression histograms of each miRNA at each time point, and statistical significance (P<0.05, P<0.01, P<0.001) was marked on the graphs.

[0077] like Figure 7 and 8As shown, compared with the control group, the expression level of hsa-miR-1303 was significantly upregulated in serum from day B30 of bed rest to day R30 of recovery from bed rest; the expression levels of hsa-miR-30a-5p and hsa-miR-181c-5p were significantly upregulated in serum at days B30, B60, and B90 of bed rest, while the expression level of hsa-miR-1275 was significantly downregulated in serum at days B30, B60, and B90 of bed rest; the expression level of hsa-miR-135b-5p was significantly upregulated in serum at days B60, B90, and R30 of bed rest. The expression level of hsa-miR-499a-5p was significantly downregulated in serum at days B60 and B90 of bed rest, while the expression level of novel-hsa-miR26-5p was significantly upregulated at days B30 and R30 of bed rest. Furthermore, the expression levels of hsa-miR-1307-3p, hsa-miR-328-3p, hsa-miR-17-5p, and hsa-miR-590-3p changed significantly at individual time points during bed rest. However, no significant changes were detected in hsa-miR-339-3p and hsa-miR-660-5p. hsa-miR-379-5p was not detected in the serum of the subjects, possibly due to its low concentration.

[0078] Figure 9 and 10 The standardized expression levels of the five candidate circulating miRNAs (hsa-miR-135b-5p, hsa-miR-590-3p, hsa-miR-499a-5p, hsa-miR-30a-5p, and hsa-miR-181c-5p) obtained from the aforementioned screening were used as test variables, and whether or not the subjects experienced weightlessness-induced bone loss was used as a state variable. Receiver Operating Characteristic (ROC) curves were plotted using SPSS 26.0. The area under the curve (AUC) and its 95% confidence interval (95% CI) for each miRNA were calculated, and the corresponding sensitivity and specificity were assessed. An AUC > 0.7 was considered clinically diagnostic, and an AUC > 0.8 was considered to have good diagnostic value.

[0079] The results are as follows Figure 9 and 10As shown, the area under the curve (AUC) calculations revealed that all five candidate miRNA biomarkers screened in the above study exhibited good diagnostic value. The AUC values ​​of hsa-miR-135b-5p, hsa-miR-181c-5p, and hsa-miR-30a-5p were all above 0.8, indicating that these three miRNAs have good diagnostic and assessment effects on weightless bone loss. The AUC value of hsa-miR-499a-5p was 0.79, indicating that it also has good diagnostic value. Additionally, the AUC of hsa-miR-590-3p was 0.73. Based on these results, we consider serum hsa-miR-30a-5p, hsa-miR-135b-5p, hsa-miR-181c-5p, and hsa-miR-499a-5p as potential biomarkers for diagnosing bone loss under simulated long-term weightlessness.

[0080] Figure 11 The main purpose was to validate the bone loss model: Eight-week-old male C57BL / 6J mice were randomly divided into a tail-suspended group and a control group. The tail-suspended group was suspended by tails with the hind limbs off the ground at a -30° head-down position for 28 consecutive days to establish a simulated microgravity model. The control group was housed normally. After 28 days of tail-suspended suspension, the bilateral femurs of the mice were dissected, and after removing soft tissue, high-resolution micro-computed tomography (μCT) was used to scan and reconstruct the distal metaphysis of the femur. Quantitative analysis was performed on bone mineral density (BMD), bone volume fraction (BV / TV), and bone microscopy. Bone microstructure parameters such as trabecular number (Tb.N), trabecular thickness (Tb.Th), trabecular separation (Tb.Sp), trabecular connection density (Conn-D), and structural pattern index (SMI) were collected. Subsequently, a three-point bending test was performed on femoral samples to record load-displacement curves and calculate biomechanical parameters such as elastic modulus, maximum stress, and elastic stress. At the same time, some femoral samples were decalcified with EDTA, embedded in paraffin, sectioned, stained with hematoxylin and eosin (HE), and the morphology and structure of trabecular bone were observed under an optical microscope.

[0081] like Figure 11 As shown, μCT scan analysis of the femur revealed that, compared to the control group, the bone mineral density (BMD), bone volume fraction (BV / TV), trabecular number (Tb.N), trabecular thickness (Tb.Th), and trabecular connectivity density (Conn-D) of the tail-suspended group significantly decreased after 28 days of tail suspension. Simultaneously, trabecular separation (Tb.Sp) and structural pattern index (SMI) significantly increased after 28 days of tail suspension, trending towards 3. The three-point bending test was used to analyze the effect of tail suspension simulating microgravity on the biomechanics of the mouse hind limb femur. The results showed that after 28 days of tail suspension, the elastic modulus, maximum stress, and elastic stress of the mouse femur all significantly decreased. Figure 11 I, J, K) indicate that simulated microgravity effects affect bone stiffness and elasticity, leading to a higher risk of fractures. HE staining results also showed that after 28 days of tail suspension, the trabeculae of the mouse femur were sparse ( Figure 11 L). The above results indicate that simulated microgravity leads to the occurrence of osteoporosis.

[0082] Figure 12 After 28 days of tail suspension, orbital blood was collected from mice in the control and tail suspension groups. After standing at room temperature, the serum was separated by centrifugation. Total RNA was extracted from the serum using the miRNeasy Serum / Plasma Kit and reverse transcribed into cDNA. qRT-PCR was performed on miR-30a-5p, miR-135b-5p, miR-181c-5p, and miR-499a-5p in the serum of each group of mice using specific primers. miR-25-3p was used as an internal reference gene for expression normalization. The relative expression level of each miRNA was calculated using the 2^(-ΔΔCt) method. The expression difference between the tail suspension group and the control group was compared using an independent samples t-test, with a significance threshold set at P<0.05.

[0083] qRT-PCR test results are as follows Figure 12 As shown, compared with the control group, the expression levels of miR-30a-5p, miR-135b-5p, and miR-181c-5p in mouse serum were significantly upregulated after 28 days of tail hanging, while the expression level of miR-499a-5p did not change significantly. These results indicate that, compared with the control group, the expression levels of miR-30a-5p, miR-135b-5p, and miR-181c-5p were significantly upregulated in serum after 28 days of tail hanging, but miR-499a-5p did not change significantly. These results suggest that miR-30a-5p, miR-135b-5p, and miR-181c-5p can serve as biomarkers for osteoporosis induced by tail hanging simulating weightlessness.

[0084] Figure 13The experiment primarily involved culturing the human osteoblast cell line MG63 on a space station during in-orbit flight. The experiment included a control group (no other treatments during spaceflight) and multiple treatment groups. The culture medium was supplemented with the bone-forming cytokine Bmp2, the actin stabilizer Jasplakinolide, a simulated 1G gravity environment, and combinations of these treatments. After in-orbit culture, the cell culture supernatant was collected from each group. Total RNA was extracted from the supernatant using the miRNeasy Serum / Plasma Kit and reverse transcribed into cDNA. Specific primers were used to quantitatively detect miR-135b-5p, miR-181c-5p, miR-30a-5p, and miR-499a-5p using qRT-PCR, and expression was normalized using appropriate internal reference genes.

[0085] The results showed that, compared with the control group (no other treatment during spaceflight), the levels of miR-135b-5p, miR-181c-5p, miR-30a-5p, and miR-499a-5p in the cell culture supernatant of each treatment group decreased, and the 1G treatment combined with the addition of Bmp2 and Jasplakinolide showed an additive effect. This indicates that promoting bone formation can inhibit the expression of these four miRNAs, and these four miRNAs can serve as biomarkers of bone metabolism during spaceflight.

[0086] Figure 14 Using two experimentally validated miRNA-target gene interaction databases, miRecords and miRTarBase, target gene prediction was performed on serum differentially expressed miRNAs (hsa-miR-17-5p, hsa-miR-181c-5p, hsa-miR-135b-5p, hsa-miR-30a-5p, hsa-miR-590-3p, hsa-miR-1303, hsa-miR-328-3p, hsa-miR-499a-5p) that were previously validated in experiments. The selection criteria were that the target genes supported by experimental validation (Reporter assay, Western blot, or qPCR, etc.) in both databases were selected. Finally, after deduplication, the experimentally validated target gene set of each miRNA was obtained, and the miRNA-target gene interaction relationship was displayed in the form of a network diagram.

[0087] The results are as follows Figure 14As shown, through joint search analysis of the miRecords and miRTarBase databases, a total of 183 experimentally validated target genes were screened from 8 differentially expressed miRNAs in serum. These target genes are involved in multiple bone metabolism-related biological processes, such as osteoblast differentiation, osteoclast activation, cytoskeleton remodeling, Wnt / β-catenin signaling pathway and TGF-β / BMP signaling pathway. This suggests that the above 8 circulating miRNAs may participate in bone metabolism imbalance under simulated weightlessness conditions by regulating the target gene network.

[0088] Figure 15 shows the GO functional enrichment analysis and KEGG pathway enrichment analysis of 183 experimental validation target genes obtained from the previous screening using the clusterProfiler package in R language. The whole genome was used as the background reference set, and the significance of enrichment was calculated using the hypergeometric distribution test. The significance threshold was set as the corrected P-value (FDR) <0.05. Functional annotation and enrichment analysis were performed on three categories: biological process (BP), cellular component (CC), and molecular function (MF). The significantly enriched GO entries were visualized using a bubble chart.

[0089] The GO results are shown in Figure 15. The target genes of these differentially expressed miRNAs are primarily involved in biological processes such as the transmembrane receptor protein serine / threonine kinase signaling pathway, cell fate determination, negative cell cycle regulation, cellular response to TGF-β stimulation, and regulation of apoptosis signaling pathways. In terms of cellular components, they are mainly involved in the formation of transcriptional regulatory complexes, focal adhesion, matrix junctions, PML bodies, etc. In terms of molecular function, they are mainly involved in DNA-binding transcription activator activity, ubiquitin-like protein ligase binding, and SMAD protein binding.

[0090] Figure 16 The KEGG pathway enrichment analysis of the 183 experimental target genes was performed using the clusterProfiler package in R. The whole genome was used as the background reference set, and the enrichment significance of each pathway was calculated using the hypergeometric distribution test. The significance threshold was set as the corrected P-value (FDR) < 0.05. Significantly enriched KEGG signaling pathways were screened, and the enrichment results were displayed in a bubble chart.

[0091] The results showed that these target genes were mainly enriched in pathways such as cellular senescence, endocrine resistance, FoxO signaling pathway, PI3K / AKT signaling pathway, thyroid hormone signaling pathway, and TGF-β.

[0092] Figure 17 Human osteoblast cell line MG63 was transfected with miR-135b-5p mimic, inhibitor-miR-135b-5p and negative control, as well as miR-181c-5p mimic, inhibitor-miR-181c-5p and negative control. 48 hours after transfection, cells were collected, total RNA was extracted and reverse transcribed into cDNA. The mRNA expression levels of Runx2, Smad5 and Sirt1 were detected by qRT-PCR. GAPDH was used as an internal reference gene for normalization. One-way ANOVA was used to compare the expression differences among the overexpression group, knockdown group and control group.

[0093] qRT-PCR test results are as follows Figure 17 As shown, overexpression of miR-135b-5p significantly reduced the mRNA expression levels of Runx2 and Smad5 in MG63 cells, while knockdown of miR-135b-5p significantly increased their expression, confirming that Runx2 and Smad5 are direct target genes of miR-135b-5p, suggesting that miR-135b-5p can participate in regulating weightless bone loss by targeting and inhibiting Runx2 and Smad5. Simultaneously, overexpression of miR-181c-5p significantly reduced Sirt1 mRNA expression, while inhibition of miR-181c-5p significantly increased Sirt1 expression, confirming that Sirt1 is a target gene of miR-181c-5p, and that Sirt1 is a NAD+ receptor agonist. + Deacetylases can maintain bone homeostasis by regulating the balance between osteoblasts and osteoclasts and promoting bone angiogenesis. Therefore, miR-181c-5p may play an important regulatory role in weightlessness-induced bone loss by targeting and inhibiting SIRT1 to disrupt bone metabolic balance.

[0094] Figure 18 Human osteoblast cell line MG63 was transfected with miR-30a-5p mimic, inhibitor-miR-30a-5p and negative control, respectively. 48 hours after transfection, cells were collected, total RNA was extracted and reverse transcribed into cDNA. The mRNA expression levels of Runx2, FoxK1 and key glycolysis genes Glut1 and Ldha were detected by qRT-PCR. GAPDH was used as an internal reference gene for normalization. The expression differences between the overexpression group, the knockdown group and the control group were compared by one-way ANOVA.

[0095] Target gene validation results are as follows Figure 18As shown, overexpression of miR-30a-5p significantly downregulated the mRNA expression level of Runx2 in MG63 cells, confirming that Runx2 is a direct target gene of miR-30a-5p, suggesting that miR-30a-5p can participate in the regulation of osteoblast differentiation by inhibiting Runx2. Combined with literature reports that miR-30a-5p can inhibit the PI3K / AKT signaling pathway to regulate aerobic glycolysis, and previous studies finding that PI3K / AKT regulates osteoblast glycolysis through FoxK1, this study further found that overexpression of miR-30a-5p significantly downregulated the expression of FoxK1 and key glycolysis genes Glut1 and Ldha, while inhibition of miR-30a-5p significantly increased the expression of these genes, showing the opposite results. These results suggest that miR-30a-5p may downregulate the aerobic glycolysis metabolic level of osteoblasts by inhibiting FoxK1 mRNA expression, thereby affecting osteoblast function and playing an important metabolic regulatory role in weightlessness-induced bone loss.

[0096] Figure 19 FoxK1-overexpressing human osteoblast cell lines were constructed and subjected to microgravity-simulated cell rotation. Cell glucose uptake, lactate, and ATP production levels were measured. Aerobic glycolysis levels and maximum glycolytic capacity were measured using a Seahorse energy metabolism analyzer. Simultaneously, conditional FoxK1 gene knockout (FoxK1 cKO) mice and control mice were constructed. 2-NBDG glucose fluorescent substitute was injected via tail vein. Mice were sacrificed 45 minutes later, and femurs were isolated. The uptake and accumulation of 2-NBDG in the trabecular bone of the femur were assessed using fluorescence microscopy.

[0097] Functional test results as follows Figure 19 As shown, FoxK1 overexpression reversed the inhibitory effect of cell rotation simulating microgravity on osteoblast glycolysis, significantly increasing glucose uptake, lactate, and ATP production levels. Seahorse analysis further confirmed that FoxK1 overexpression could improve the level of aerobic glycolysis and maximum glycolytic capacity in osteoblasts, while inhibiting FoxK1 reduced the level of cellular glycolysis. In vivo experiments showed that the 2-NBDG fluorescence signal in the femoral trabecular bone of FoxK1 cKO mice was significantly weakened, indicating that the uptake of glucose by osteoblasts in knockout mice was significantly reduced. The above results further confirm that FoxK1 is a key upstream regulator of osteoblast glycolysis, and under simulated microgravity conditions, it can affect osteoblast function and bone formation by regulating aerobic glycolysis metabolism.

[0098] Figure 20Conditional FoxK1 knockout (FoxK1 cKO) mice and littermate control mice were constructed, and a tail-suspended microgravity simulation experiment was performed to model the process. After separating the bilateral femurs, high-resolution μCT scanning was used to analyze bone microstructure parameters such as bone mineral density (BMD), bone volume fraction (BV / TV), trabecular number (Tb.N), trabecular thickness (Tb.Th), trabecular connectivity density (Conn-D), trabecular separation (Tb.Sp), and structural pattern index (SMI). Subsequently, a three-point bending test was performed on femoral samples to detect biomechanical indicators such as elastic modulus, maximum stress, and elastic stress. RNA was extracted from femoral tissue and reverse transcribed. qRT-PCR was used to detect the mRNA expression levels of bone formation marker genes such as Runx2, Osterix, Collagen1, and OCN. GAPDH was used as an internal reference for normalization. One-way ANOVA was used to compare the differences between the knockout group and the control group.

[0099] μCT analysis showed that, compared with the control group, the bone mineral density (BMD), bone volume fraction (BV / TV), trabecular number (Tb.N), trabecular thickness (Tb.Th), and trabecular connectivity density (Conn-D) of the femur in FoxK1 cKO mice were significantly decreased, while trabecular separation (Tb.Sp) and structural pattern index (SMI) were significantly increased, suggesting that FoxK1 deficiency leads to bone microstructural degeneration and osteoporosis-like changes. The three-point bending test further showed that the elastic modulus, maximum stress, and elastic stress of the femur in knockout mice were significantly decreased, indicating that FoxK1 deficiency impairs the biomechanical properties of the bone. Meanwhile, The mRNA expression levels of key bone formation genes such as Runx2, Osterix, Collagen1, and OCN were significantly downregulated in the femur of knockout mice. These results indicate that FoxK1 affects bone formation by regulating osteoblast glycolysis, while miR-30a-5p can downregulate osteoblast glycolysis and bone formation by targeting and inhibiting FoxK1. This miR-30a-5p plays an important cascade regulatory role in weightlessness-induced bone loss and provides experimental evidence for a deeper understanding of the molecular mechanisms of the miR-30a-5p / FoxK1 / glycolysis axis in bone metabolism regulation.

[0100] In summary, this invention simulates long-term weightlessness through a 90-day -6° head-down bed rest experiment. Combining Mfuzz temporal clustering analysis, differential expression analysis, correlation analysis of bone mineral density and bone metabolism indicators, Lasso regression screening, and ROC curve validation, a multi-level bioinformatics analysis method was used to screen a diagnostic combination of three biomarkers—miR-30a-5p, miR-135b-5p, and miR-181c-5p—from 937 circulating serum miRNAs. This combination exhibited AUC values ​​of 0.86, 0.93, and 0.93, respectively, demonstrating extremely high diagnostic sensitivity and specificity. A standardized detection system was established using miR-25-3p as an internal reference gene and cel-miR-39 as an exogenous quality control. Dual validation was achieved using a ground-based tail-suspended mouse model (28 days of hind limb de-loading) and a human osteoblast MG63 culture experiment carried out on a space station. This study, for the first time, confirmed the specific secretion changes of this biomarker combination under microgravity conditions, and showed that its secretion level was negatively correlated with bone formation status. The study revealed the regulatory mechanism of this biomarker combination in bone metabolism: miR-135b-5p inhibits osteogenic differentiation by targeting Runx2 and Smad5; miR-181c-5p regulates bone homeostasis by targeting Sirt1; and miR-30a-5p affects osteoblast energy metabolism through the FoxK1 / glycolysis axis, providing a new target for interventional treatment of spatial bone loss.

[0101] It will be readily understood by those skilled in the art that the above-described advantageous methods can be freely combined and superimposed without conflict. The above are merely preferred embodiments of this application and are not intended to limit this application. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the protection scope of this application. The above are merely preferred embodiments of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of this application, and these improvements and modifications should also be considered within the protection scope of this application.

Claims

1. A circulating miRNA biomarker for the diagnostic assessment of spatial bone loss, characterized in that, The markers include miR-30a-5p, miR-135b-5p, and miR-181c-5p.

2. The marker according to claim 1, characterized in that, The AUC value of the combined detection of miR-30a-5p, miR-135b-5p and miR-181c-5p is greater than 0.

8.

3. The marker according to claim 1, characterized in that, The markers also include miR-499a-5p.

4. The use of the biomarker according to any one of claims 1-3 in the preparation of products for the diagnosis or assessment of spatial bone loss.

5. A diagnostic kit for assessing spatial bone loss, characterized in that, include: Primers or probes for amplifying the cDNA of each miRNA in the markers described in any one of claims 1-3, primers or probes for internal reference genes, primers or probes for exogenous quality control genes, reverse transcription reagents, PCR reaction solution, water, and buffer.

6. The detection kit according to claim 5, characterized in that, The primers used to amplify the cDNA of each miRNA in the markers described in any one of claims 1-3 shall have their upstream primer sequences determined as follows: the accurate sequence of the corresponding miRNA is obtained from the miRbase database, and the base U in the sequence is replaced with T.

7. The detection kit according to claim 5, characterized in that, The internal reference gene is selected from at least one of miR-25-3p, miR-16-5p, and miR-451a.

8. The detection kit according to claim 5, characterized in that, The exogenous quality control genes are cel-miR-39 and / or Arabidopsis thaliana miR-159a.

9. The detection kit according to claim 5, characterized in that, The test samples for the test kit are serum, plasma, urine, or saliva.

10. The detection kit according to claim 5, characterized in that, When the test sample for the test kit is serum or plasma, the volume of peripheral blood sample used is 250μL~500μL.

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