Patients diagnosed with AL after THA (n=8) who underwent revision surgery at the Department of Orthopedics of Henan Provincial People's Hospital (Zhengzhou, China) from May to October 2023 were selected as AL group and patients (n=8) diagnosed with avascular necrosis of femoral head (ANFH) or femoral neck fracture who underwent primary THA in the same time period were selected as control group. Inclusion criteria for AL were as follows: i) History of THA surgery; ii) persistent hip pain, limited activity and other symptoms (such as muscle atrophy) after THA; iii) radiological examination (such as X-ray, CT or MRI) shows a radiolucent line or other signs of loosening around the prosthesis and iv) clinical and laboratory examination rule out infection, trauma or other causes of prosthesis loosening (13). Exclusion criteria were as follows: i) Prosthesis loosening caused by postoperative infection, trauma or other diseases (such as bone tumors, systemic lupus erythematosus); ii) postoperative time <6 months (before stable evaluation period) and iii) severe systemic disease that prevents further treatment. Inclusion criteria for controls were as follows: i) Radiological examination (such as X-ray or MRI) shows typical signs of ANFH or femoral neck fracture and ii) clinical examination reveals typical symptoms (ANFH, pain in the groin, limited internal rotation and abduction activities, positive patrick sign; femoral neck fracture: hip pain, limitation of movement, deformity of lower limb, and shortening of affected limb). Exclusion criteria were as follows: i) Hip pain and functional impairment caused by other disease (such as hip infection or tumor); ii) severe systemic inflammatory disease, such as rheumatoid arthritis or systemic lupus erythematosus; iii) severe neurological disease; iv) severe systemic diseases that prevent further treatment and v) mental health issues that prevent treatment and assessment. The samples from patients with AL were collected within 3 months of the onset of loosening symptoms upon completion of diagnosis and revision surgery. The samples of the control group were taken during primary THA surgery. Both AL and control group samples were derived from the surrounding tissue of the liner/head/stem junction of the prosthesis, ensuring consistency in tissue sampling.

The present study was conducted according to the principles of the 1975 Declaration of Helsinki and approved by the Medical Ethics Committee of the Henan Provincial People's Hospital (approval no. 2022-68). All participants provided written informed consent to participate.

A total of eight pairs of tissue samples were collected for metabolomics analysis and a 4:1 solution of methanol to water was added to the tissue sample. The samples were ground using a grinder for 6 min (−10°C; 50 Hz), followed by low-temperature ultrasound extraction for 30 min (5°C; 40 kHz). The samples were stored at −20°C for 30 min and centrifuged for 15 min (4°C, 13,000 × g); supernatant was transferred to an injection vial with an internal tube for analysis. The instrument used for liquid chromatography-mass spectrometry (LC-MS) analysis was UHPLC-Q Active system, with an HSST3 chromatographic column (100.0×2.1 mm; internal diameter, 1.8 µm; flow rate of 0.5 ml/min). The sample MS signal was collected in positive and negative ion scanning modes with the following settings: Mass scanning range, 70–1,050 m/z; positive ion voltage 3,500; negative ion voltage 2,800 V; sheath gas, 40 psi; auxiliary heating gas, 10 psi; ion source heating temperature, 400°C; cycle collision energy, 20–60 V; MS1 resolution, 70,000 and MS2 resolution, 17,500 full width at half maxima.

Raw LC-MS data were imported into Progenesis QI metabolomics processing software (version 2.0, Waters Corporation) for analysis, while MS and MS/MS information was integrated with human metabolome database public metabolic database (hmdb.ca/) and Metlin (metlin.scripps.edu/) and matched with Majorbio database (majorbio.com/). The response intensity of sample MS peaks was normalized using the sum normalization method to obtain the normalized data matrix (14). Variables with relative standard deviation >30% were removed from the quality control samples and log10 logarithmization was performed to obtain the final data matrix for analysis using the R package ropls (version 1.6.2) for principal component analysis (PCA) and orthogonal least squares discriminant analysis (OPLS-DA) (15). Metabolites with variable importance (VIP)>1 and P<0.05 (assessed by unpaired student's t test) obtained from the OPLS-DA model were considered differential metabolites. MetaboAnalyst (Version 5.0) was used for metabolic pathway analysis based on the KEGG and The Small Molecule Pathway Database (SMPDB) databases (16).

Following tissue grinding as aforementioned, TRIzol (cat. no. 15596018CN, Invitrogen) was added to extract RNA, Oligo dT (cat. no. 18418012, Invitrogen) was used to enrich mRNA, fragmentation buffer was added; mRNA was randomly broken into small fragments of ~300 bp and reverse-transcribed using Hieff NGS ds-cDNA Synthesis Kit (cat. no. 13488ES96, Yeasen); EndRepairMix (cat. no. N203-01/02, Vazyme) was added to supplement the flat end. Next, A base was added at the 3′ end to connect the Y-shaped junction. cDNA purification and fragment sorting that utilize beads to selectively bind and isolate the 200–300 bp of DNA fragments were done using sorting kits (cat. no. 12601ES56, Hieff NGS^® DNA Selection Beads, Yeasen). The sorted products were used for amplification by PCR using Phusion Hot Start II High-Fidelity DNA Polymerase (cat. no. F565L, Thermo Fisher Scientific). Forward primer: 5′-AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTCTTCCGATCT-3′, reverse: 5′-CAAGCAGAAGACGGCATACGAGATCGGTCTCGGCATTCCTGCTGAACCGCTCTTCCGATCT-3′. Thermo cycling conditions were as follows: Initial denaturation: 98°C for 30 sec to denature the double-stranded DNA, denaturation: 98°C for 15 sec to separate the DNA strands, annealing: 55°C for 30 seconds, elongation: 72°C for 30 sec, 30 cycles, and final extension: 72°C for 5 min. Prepared libraries were performed by VAHTS Universal Plus DNA Library Prep Kit for Illumina (cat. no. ND617-01/02, Vazyme) according to the manual. Qubit 2.0 (Invitrogen; Thermo Fisher Scientific, Inc.) was used to detect the concentration of the library, and the loading concentration of the library were pooled at 10 nM concentration, we performed the 2×150 bp paired-end sequencing (PE150) and an average read depth of 15 million read pairs/library on Illumina NovaSeq X Plus platform (Illumina, Inc.) following the vendor's recom-mended protocol. Illumina BaseSpace (Version: V5.2.0, illumina.com/software/basespace.html) for base calling and demultiplexing. Trimmomatic (Version: V0.39, usadellab.org/cms/?page=trimmomatic) for quality trimming of sequence reads. STAR (Version: V2.7.3a, URL: http://github.com/alexdobin/STAR) for aligning reads to a reference genome.

DESeq2 (Version 1.24.0; bioconductor.org/packages/stats/bioc/DESeq2/) with a screening threshold of |log2FC|≥1 and P_adj<0.05 was used to identify differentially expressed genes (DEGs). Functional enrichment analyses included Kyoto Encyclopedia of Genes and Genomes (KEGG; Version 2022.10; genome.jp/kegg/), Gene Ontology (GO; goatools; Version 0.6.5; files.pythonhosted.org/packages/bb/7b/0c76e3), Reactome (Version 82; reactome.org) and Disease Ontology (DO; disease-ontology.org) enrichment analyses. The screening threshold for determining significant differences in transcript expression between samples was determined by DESeq2, with P_adj<0.05. P-value was corrected using the Benjamini-Hochberg method. P_adj<0.05 was considered to indicate significant enrichment.

The tissue samples were ground as aforementioned to extract protein and concentration was measured using the BCA method. Enzymatic alkylation was performed by adding iodoacetamide (10 mM, room temperature for 30 min) to protein. Adding DL-Dithiothreitol (DTT, 50 mM, room temperature for 15 min) to quenching the reaction to generate stable and specific peptides for mass spectrometry analysis. Enzymatic alkylation was performed on 100 µg samples; the next day, samples were subjected to tandem mass tag labeling and mixing, mixed with an equal amount of labeled products in a tube, dried with a vacuum concentrator (30°C, 20 min) and the peptide samples were dissolved in Ultra Performance Liquid Chromatography buffer (Waters Corporation). Next, high-pH liquid-phase separation was performed using a reverse-phase C18 column and the two-dimensional Easy-nLC1200 result was analyzed by using a QExactive (Thermo Fisher Scientific, Inc.) mass spectrometer. The peptide segments were dissolved in MS loading buffer (Thermo Fisher Scientific, Inc.) and subjected to separation in a C18 chromatography column (35°C, 5 µl, 75 µMx25 cm; Thermo Fisher Scientific, Inc.) for 120 min at a flow rate of 300 µl/min. The process was based on EASY-nLC liquid-phase gradient elution [phase A, 2% acetonitrile (with 0.1% formic acid) and B, 80% acetonitrile (with 0.1% formic acid)] with the following settings: 0–1 min, 0–5% B; 1–63 min, 5–23% B; 63–88 min, 23–48% B; 88–89 min, 48–100% B and 89–95 min, 100% B. MS and MS/MS modes were switched automatically for collection, with MS resolutions of 70 and 35 K, respectively. With each MS full scan (m/z, 350–1,300), the top 20 parent ions were selected for secondary fragmentation, with dynamic exclusion time of 18 sec.

The original files were analyzed by using ProteomeDiscoverer™ (version 2.2; Thermo Fisher Scientific, Inc.). The false discovery rate for peptide identification during the search process was ≤0.01. The t test function in R software (search.r-project.org/CRAN/refmans/DACF/html/lw.t.test.html; version 1.6.2) was used to calculate the significance of the inter-sample differences, as well as the fold-change (FC) of the inter-group differences. The screening criteria for significantly differentially expressed proteins were P<0.05 and FC >1.2 for up- and FC <0.83 for downregulated proteins. Functional annotation and metabolic pathway analysis were performed on all differentially expressed proteins. GO enrichment analysis was performed using Goatools (Version no. 1.4.4; pypi.org/project/goatools/) and Fisher's exact test. Based on Meiji's independently developed process, KEGG pathway enrichment analysis was performed (17). P_adj<0.05 was considered to indicate significant enrichment.

Using Cytoscape (version 3.9.1; js.cytoscape.org/), a network of genes, proteins and metabolic compounds was constructed to identify pathways significantly enriched according to DEGs and reveal potential regulatory mechanisms between genes and metabolites. Differential metabolites and DEG expression data between the AL and control group were imported into Cytoscape to assess genetic and metabolic changes in AL, as well as the potential mechanisms of metabolism.

DESeq2 (Version 1.24.0; bioconductor.org/packages/stats/bioc/DESeq2/) was used for differential gene analysis. KEGG (Version 2022.10; genome.jp/kegg/), GO (goatools; Version 0.6.5; files.pythonhosted.org/packages/bb/7b/0c76e3) and Reactome databases (Version 82; reactome.org/) were used to determine signal transduction pathways related to the DEGs. DO database (https://disease-ontology.org) was used to determine human diseases associated with DEGs, while the GO and KEGG databases were used for protein functional annotation and functional enrichment. R software (Version1.6.2) was used for differential protein analysis in sample tissues. MultiLoc2 (Version 2.0) was used for subcellular localization analysis (18). Differential metabolite analysis was performed with ropls (master.bioconductor.org/packages/stats/bioc/ropls/; R package; Version1.6.2) and multivariate statistics with scipy (https://www.scipy.org/; Python; Version1.0.0) based on KEGG pathway enrichment results of the human metabolism, metabolic disease and metabolite signaling pathways associated with differential metabolite enrichment.

Total RNA from AL samples and controls was isolated using TRIzol (Thermo Fisher Scientific, Inc.). RNA was subjected to phenol-chloroform extraction for purification. The quantity and quality of the purified RNA were assessed by measuring the absorbance at 260/280 nm (acceptable ratio ≤1.8 and ≥2.2) using Microplate Reader (Thermo Fisher Scientific, Inc.). cDNA was synthesized using HiScript II RT SuperMix (Vazyme Biotech Co., Ltd.) at 37°C for 15 min and 85°C for 5 sec and maintained at 4°C. RT-qPCR was conducted with AceTaq DNA Polymerase (Vazyme Biotech Co., Ltd.) as follows: Initial denaturation at 95°C for 1 min, followed by 40 cycles of 95°C for 10 sec and 60°C for 30 sec. Each transcript concentration was normalized to the level of GAPDH using the 2^−ΔΔCq method (19). The primer sequences were as follows: GAPDH forward, 5′GGAGCGAGATCCCTCCAAAAT-3′ and reverse, 5′-GGCTGTTGTCATACTTCTCATGG-3′; cytokine receptor-like factor-1 (CRLF1) forward, 5′-CTCTCCCGTGTACTCAACGC-3′ and reverse, 5′-GGGCAGGCCAACATAGAGG-3′ and glutathione-S transferase µ1 (GSTM1) forward, 5′-GCCCATGATACTGGGGTACTG-3′ and reverse, 5′-GGGCAGATTGGGAAAGTCCA-3′.

Samples from patients with AL and controls were collected and lysed in RIPA buffer (Merck KGaA) on ice for 30 min. Protein concentration was determined using the BCA method. A total of 20 µg/lane protein samples were separated by 10% SDS-PAGE and transferred onto PVDF membranes (MilliporeSigma). The membrane was blocked with 5% skimmed milk at room temperature for 2 h. Subsequently, the membrane was incubated overnight at 4°C with primary antibodies targeting CRLF1 (1:1,000; 43 kDa; cat. no. bs-8663R; Beijing Biosynthesis Biotechnology Co., Ltd.), GSTM1 (1:2,000; 27 kDa; cat. no. 12412-1-AP; Wuhan Sanying Biotechnology) and GAPDH (1:10,000; 36 kDa; cat. no. HRP-60004; Wuhan Sanying Biotechnology). Horseradish peroxidase-conjugated secondary antibodies (1:5,000; cat. no. I1904-65C; Shanghai Univ Biotechnology Co., Ltd.) were incubated at room temperature for 2 h. Signal analysis was performed using enhanced chemiluminescence reagent (cat. no. BL520A, Biosharp) and an image analyzer (Bio-Rad Laboratories) to detect protein expression levels, and Image Lab software (Bio-Rad Laboratories; Version 6.1). The intensity of each band was quantified using AlphaEaseFC software.

Data were analyzed using GraphPad Prism (version 6.01; Dotmatics). Continuous variables that conform to normal distribution are presented as the mean ± standard deviation of ≥3 independent experimental repeats and were tested using unpaired Student's t-test. Categorical variables were tested using χ² test. Pearson correlation analysis was performed between CRLF1, GSTM1 and differential metabolites. P<0.05 was considered to indicate a statistically significant difference.

All patients presented with unilateral onset of AL and had undergone unilateral surgery. Of patients with AL who had undergone revision surgery, reasons for the initial total hip replacement included ANFH in six cases and femoral neck fracture in two cases. The friction interface of the initial replacement surgery in the AL group was ceramic on polyethylene in six cases and metal on polyethylene in two cases. The initial prosthesis fixation types in the AL group were cementless in seven cases and cemented in one case; in the latter, the femoral stem was cemented and the acetabular cup cementless, the acetabular cup did not loosen, but the femoral stem prosthesis did. In all cases in the AL group, prosthesis failure due to infection was excluded. AL group consisted of six females and two males, with a mean age of 60.75±3.62 years. The average duration from the initial replacement surgery to the revision surgery in the AL group was 109.5±62.99 months. In the AL group, there were three cases of isolated acetabular cup loosening, one case with isolated femoral stem loosening and four cases with the loosening of both the acetabular cup and femoral stem.

In the control group, reasons for surgery included ANFH in five cases and femoral neck fracture in three cases. The control group consisted of six females and two males, with an average age of 61.88±2.29 years. There were no significant differences in sex ratio or the average age between the two groups (Table I).

There were 454 DEGs in the AL vs. control groups (Table SI), 33 of which were up- and 421 were downregulated. Triadin, which is associated with muscle contraction (20), was the most significantly downregulated gene in patients with AL. PRKY gene was significantly upregulated in the AL group (Fig. 1A). To determine molecular functions (MFs) affected by differential gene expression, the KEGG database was used. A total of 17 enriched KEGG pathways were identified, including ‘cardiac muscle contraction’, ‘hypertrophic cardiopathy’ and ‘dilated cardiopathy’ (Fig. 1B). By mapping DEGs to GO database for analysis, it was revealed that there may be an association between AL and genes involved in the regulation of the ‘troponin complex’, ‘transition between fast and slow fiber’, ‘cellular response to purine-containing compound’, ‘response to stimulus involved in regulation of muscle adaptation’, ‘telethonin binding’ and ‘FATZ binding’ (Fig. 1C). Reactome database revealed significant changes in reactions and biological pathways such as ‘muscle contraction’, ‘transport of small molecules’ (Fig. 1D). DO showed enrichment of genes associated with diseases such as ‘intrinsic cardiopathy’, ‘cardiomyopathy’ and ‘heart disease’ (Fig. 1E).

Between AL and control, there were 133 differentially expressed proteins, 107 of which were up- and 26 were downregulated (Fig. 2A). The most significant downregulation in the AL group was cyclin-dependent kinase 9 protein, which is associated with osteoclastogenesis and bone resorption activity (21). The expression of proline rich coiled-coil 2C protein was significantly upregulated (Fig. 2A). KEGG enrichment analysis indicated nine significantly enriched KEGG pathways, including ‘NOD-like receptor signaling pathway’, ‘osteoclast differentiation’, and ‘Shigellosis’. (Fig. 2B). In GO, ‘macromolecule biosynthetic process’, ‘cytoplasmic ribonucleoprotein granule’, and ‘antigen processing and presentation’ were enriched (Fig. 2C). Subcellular localization analysis elucidates the specific cellular localization of differential proteins, which is closely related to protein function (22). The differentially expressed proteins were primarily located in the cytoplasmic, nuclear and mitochondrial regions (Fig. 2D).

PCA (Fig. 3A) and OPLS-DA (Fig. 3B) showed significant separation and metabolic changes. According to VIP >1.5, 113 significant differential metabolites were screened, including 95 up- and 18 downregulated. Dextrophan O-glucuronide was significantly downregulated and caprylic acid was significantly upregulated, with the highest VIP value of 4.32 (Fig. 3C and D). KEGG annotation showed differential compounds were primarily associated with metabolism (Fig. 3E), with significant enrichment of ‘glycine, serine and threonine metabolism’, ‘phenylalanine metabolism’, ‘glyoxylate and dicarboxylate metabolism’, ‘tyrosine metabolism’ and ‘arginine and proline metabolism’ (Fig. 3F). Differential expression of GSTM1 and CRLF1 was consistent at the mRNA and protein levels (Fig. 4A). Pearson correlation analysis between CRLF1 and GSTM1 genes and differential metabolites showed that these genes were associated with changes in 44 metabolites (Fig. 4B). SMPDB (Fig. 4C) and KEGG enrichment analysis (Fig. 4D) showed that CRLF1 and GSTM1 affected ‘pyruvate metabolism’, ‘citrate cycle (TCA cycle)’, ‘tyrosine metabolism’, ‘purine metabolism’, ‘valine, leucine and isoleucine degradation’, ‘arginine and proline metabolism’, ‘phenylalanine, tyrosine and tryptophan biosynthesis’. Corresponding metabolites of associated pathways, such as malic acid, guanine, L-tyrosine, niacinamide, L-valine, L-proline, L-isoleucine and L-phenylalanine were increased (Fig. 4E).

Pathway analysis was conducted at the transcriptional, protein and metabolite levels and KEGG enrichment revealed common pathways regulated at transcriptional, protein and metabolite levels, with 24 pathways in the AL group (Fig. 5). The ‘arginine and proline metabolism’, ‘purine metabolism’ and ‘glutathione metabolic pathways’ were regulated at the transcriptional, protein and metabolite levels in AL. The metabolites guanosine 3′-monophosphate, deoxyguanylic acid, adenosine 3′-monophosphate, guanine, L-glycine and adenosine were significantly overexpressed in the AL group, participating in the ‘purine metabolic pathway’ and affecting expression levels of the guanine deaminase (GDA), Adenylosuccinate Synthase 1 (ADSS1), Adenosine Monophosphate Deaminase 1 (AMPD1), Adenylate Kinase 1 (AK1), Adenylate Cyclase 2 (ADCY2) and 5′-Nucleotidase, Cytosolic IA (NT5C1A) genes and the 5′-Nucleotidase Ecto (NT5E) and Deoxyguanosine Kinase (DGUOK) proteins. The ‘arginine and proline metabolic pathway’ is a key pathway in AL, in which the metabolic levels of 1-pyroline-2-carboxylic acid and protein expression of Leucine Aminopeptidase 3 (LAP3) was increased, and gene expression of the nitric oxide synthase 1 (NOS1), Creatine Kinase M-Type (CKM), 4-Hydroxy-2-Oxoglutarate Aldolase 1 (HOGA1), Carnosine Synthase 1 (CARNS1) and Creatine Kinase, Mitochondrial 2 (CKMT2) genes were downregulated. The ‘glutathione metabolic pathway’ is also one of the important pathways in AL, in which the expression level of the L-glycine metabolite was significantly increased, the gene and protein expression levels of GSTM1 were significantly reduced, the LAP3 protein expression level was significantly increased, and the gene expression level of MGST1 was significantly reduced (Fig. 5).

DEG verification was conducted using RT-qPCR and western blotting to measure mRNA and protein expression levels of CRLF1 and GSTM1 in tissue samples. The results showed that, compared with the control group, the mRNA expression of CRLF1 and GSTM1 in AL (Fig. 6A and B), as well as protein expression (Fig. 6C-E), was significantly decreased.