Identification of BTBD7_hsa_circ_0000563 as a circRNA

To verify that BTBD7_hsa_circ_0000563 is a circular RNA, we designed divergent primers that specifically amplified the back-spliced forms of BTBD7. The “head-to-tail” splicing of BTBD7_hsa_circ_0000563 in the PBMCs of 4 CAD patients was confirmed via Sanger sequencing (Fig. 1). Moreover, the clinical and demographical characteristics of subjects undergoing BTBD7_hsa_circ_0000563 circularization validation are presented in Table 2.

Fig. 1

The cyclization site confirmed by Sanger sequencing

Table 2 Baseline characteristics of the subjects grouped according to various populations Validation of BTBD7_hsa_circ_0000563 expression levels

To verify the connection between BTBD7_hsa_circ_0000563 levels and CAD, the expression level of BTBD7_hsa_circ_0000563 in PBMCs was measured via qRT–PCR in a large population (210 CAD patients and 24 control individuals). The clinical and demographical characteristics of the samples undergoing BTBD7_hsa_circ_0000563 expression validation are presented in Table 2. The expression level of BTBD7_hsa_circ_0000563 in the PBMCs of CAD subjects and control individuals is presented in Table 3. In general, BTBD7_hsa_circ_0000563 showed significantly lower expression levels in CAD patients than in control individuals (P = 0.002, Fig. 2 A).

Table 3 The expression levels of BTBD7_hsa_circ_0000563 in the validation population Fig. 2

The expression level and the ROC curve of BTBD7_hsa_circ_0000563. (A) The expression level of BTBD7_hsa_circ_0000563 in the CAD group was significantly lower than that in the control group (**: P < 0.01). (B) ROC curve analysis of BTBD7_hsa_circ_0000563. (C) ROC curve analysis of BTBD7_hsa_circ_0000563 with conventional risk factors. (D) The expression level of BTBD7_hsa_circ_0000563 stratified based on sex (*: P < 0.05, ns: P > 0.05). (E) ROC curve analyses of BTBD7_hsa_circ_0000563 based on sex. CAD, coronary artery disease; ROC, receiver-operator characteristic; AUC, area under the receiver-operator characteristic curve

Given the difference in sex distribution between the CAD group and control group, we stratified the data based on sex and analysed it again. In males, the expression level of BTBD7_hsa_circ_0000563 in the CAD group was still significantly lower than that in the control group (P = 0.020, Fig. 2D). However, in females, the expression level of the circRNA was not significantly different between the two groups (P = 0.158, Fig. 2D). Nevertheless, the expression level of BTBD7_hsa_circ_0000563 still showed a downwards trend in female CAD patients.

Correlations between BTBD7_hsa_circ_0000563 expression levels and the clinical and demographical characteristics

To test whether the expression level of BTBD7_hsa_circ_0000563 was correlated with cardiac risk factors and conventional CAD diagnostic markers, we conducted Spearman’s correlation analysis. The results (Table 4) showed that the expression level of BTBD7_hsa_circ_0000563 was associated with the Gensini score (coefficient = -0.130, P = 0.046), which indicates that BTBD7_hsa_circ_0000563 might participate in the progression of CAD.

Table 4 Correlations between the baseline characteristics and circRNA levels in the subjects Confirming BTBD7_hsa_circ_0000563 as an independent predictor for CAD

To explore the predictive value of BTBD7_hsa_circ_0000563 for CAD, we divided the subjects into quarters based on the interquartile range of the circRNA expression level. As presented in Table 5, univariate logistic regression analysis showed that the level of BTBD7_hsa_circ_0000563 was inversely associated with CAD without adjustment (OR = 0.518, 95% CI: 0.334–0.802, P = 0.003). After adjusting for the impact of other risk factors, an independent negative correlation between BTBD7_hsa_circ_0000563 and CAD was still observed (OR = 0.509, 95% CI: 0.304–0.851, P = 0.010). These results identify BTBD7_hsa_circ_0000563 as an independent predictor for CAD.

Table 5 Univariate and multivariate logistic regression analysis to identify this circRNA as an independent predictor of CAD Diagnostic potential of BTBD7_hsa_circ_0000563

The area under the ROC curve (AUC) for the BTBD7_hsa_circ_0000563 level in predicting CAD was 0.690 (95% CI: 0.613–0.766, P = 0.002, Fig. 2B). Due to the complex aetiology of CAD, we introduced conventional markers and risk factors for CAD (including sex, age, BMI, smoking status, fasting blood glucose level, and HDL level) into the ROC curve model. After that, the AUC increased to 0.767 (95% CI: 0.659–0.874, P < 0.001, Fig. 2 C), with a sensitivity of 0.7447 and specificity of 0.8421. These findings may shed light on the value of BTBD7_hsa_circ_0000563 as a biomarker for CAD diagnosis, especially after being combined with conventional markers and risk factors.

Furthermore, we conducted ROC analyses for BTBD7_hsa_circ_0000563 in females and males separately due to the difference in sex distribution. In males, the AUC was 0.709 (95% CI: 0.596–0.821, P = 0.021, Fig. 2E), and in females, the AUC was 0.628 (95% CI: 0.501–0.755, P = 0.154, Fig. 2E). BTBD7_hsa_circ_0000563 showed good diagnostic value for CAD in males, although the diagnostic potential of BTBD7_hsa_circ_0000563 in females remains to be further studied.

Proteins bound to BTBD7_hsa_circ_0000563

BTBD7_hsa_circ_0000563 was significantly retrieved from chromatin with the BTBD7_hsa_circ_0000563 probes compared to LacZ probes (P < 0.001, Fig. 3 A). In addition, the BTBD7_hsa_circ_0000563 probes did not retrieve GAPDH (P < 0.001, Fig. 3 A). The results above demonstrated the specificity and accuracy of the probes.

Fig. 3

Verification of circRNA probes and ChIRP products (A) qRT–PCR results verifying the specificity and accuracy of the BTBD7_hsa_circ_0000563 probes. (B) The results of silver staining assay for ChIRP products. CAD, coronary artery disease; ChIRP, chromatin isolation by RNA purification

The silver staining assay for ChIRP products, including input, target, Lacz and bead groups, was conducted. The results of silver staining showed that differential bands actually existed between the target groups and all control groups (LacZ and bead groups) (Fig. 3B), indicating that the products of the ChIRP assay in the present study are highly specific at the proteome level.

A total of 134 peptides were identified with FDR < 0.7% via PEAKS Studio after the LC–MS/MS assay. The peptide-spectrum matches (PSM) score can evaluate the similarity between actual and theoretical spectra. The distribution of PSM scores (Figure S1a) showed that all error spectra had scores below 33.5. Therefore, we set the filter criteria for peptides to have a PSM score greater than 33.5. Simultaneously, the distribution of mass accuracy (Figure S1b) showed that the mass accuracy of the target spectra was approximately 0, which indicated high accuracy. The analyses above can guarantee the reliability of the peptide.

After removing contaminating proteins, such as keratin and serum albumin, seven proteins were identified to interact with BTBD7_hsa_circ_0000563 directly through the ChIRP-MS assay (Table 6). Six proteins were harvested from the 20 PBMC samples of control individuals, and 1 protein was harvested from the 18 PBMC samples of CAD patients.

Table 6 Proteins bound to BTBD7_hsa_circ_0000563 GO enrichment analysis

To further explore the possible biological and functional activities of the 7 proteins bound to BTBD7_hsa_circ_0000563, GO analyses were conducted with adjusted P < 0.05. In accordance with the GO enrichment results, 199 biological process terms, 27 cellular component terms, and 7 molecular function terms were enriched. The results demonstrated that the top three biological processes in which these proteins participated included error-prone translesion synthesis, nucleotide-excision repair, DNA duplex unwinding, and error-free translesion synthesis (Fig. 4 A). The cellular component of these proteins was mainly derived from the mitochondrial outer membrane, organelle outer membrane, and outer membrane (Fig. 4B). Furthermore, in the molecular function category, these proteins were involved in protein tag, ubiquitin protein ligase binding, and ubiquitin-like protein ligase binding (Fig. 4 C).

Fig. 4

Bioinformatic analyses of proteins bound to BTBD7_hsa_circ_0000563. (A) The top 10 biological process terms of Gene Ontology (GO) analysis for proteins bound to BTBD7_hsa_circ_0000563. (B) The top 10 cellular component terms of GO analysis for proteins bound to BTBD7_hsa_circ_0000563. (C) The 7 molecular function terms of GO analysis for proteins bound to BTBD7_hsa_circ_0000563. (D) The Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis results of proteins bound to BTBD7_hsa_circ_0000563. (E) The protein–protein interaction (PPI) networks of proteins bound to BTBD7_hsa_circ_0000563. UBB, polyubiquitin-B; UBC, polyubiquitin-C; UBA52, ubiquitin-60 S ribosomal protein L40; RPS27A, ubiquitin-40 S ribosomal protein S27a; ARG1, arginase-1; CTSD, cathepsin D; PCCA, propionyl-CoA carboxylase alpha chain mitochondrial

KEGG enrichment analysis

In accordance with the KEGG enrichment analysis, the proteins bound to BTBD7_hsa_circ_0000563 were involved in a total of 8 pathways. The eight enriched pathways were mitophagy – animal, ubiquitin mediated proteolysis, Kaposi sarcoma-associated herpesvirus infection, Shigellosis, Parkinson disease, pathways of neurodegeneration - multiple diseases, ribosome, and coronavirus disease - COVID-19 (Fig. 4D).

Protein–protein interaction networks

To further explore the potential interactions between the proteins bound to BTBD7_hsa_circ_0000563, PPI prediction was performed (Fig. 4E). The PPI network showed 7 nodes and 7 edges, in which ubiquitin-60 S ribosomal protein L40, ubiquitin-40 S ribosomal protein S27a, polyubiquitin-B, and polyubiquitin-C interacted with each other directly, and arginase-1 also closely interacted with cathepsin D. However, the propionyl-CoA carboxylase alpha chain had no connection with other proteins. These PPI prediction results suggest that the proteins bound to BTBD7_hsa_circ_0000563 cooperated with each other to a certain extent and that the first four proteins listed above were the most closely related proteins.

Validation of UBB (polyubiquitin-B) expression levels

To find out the hub protein, -10lgP–values and interaction scores of proteins were taken into consideration (Table S1, Additional file 2). Herein, we found 4 possible key proteins including UBB, UBC, RPS27A, and UBA52. In addition, polyubiquitination is a critical modification in mitophagy[19] and Razeghi’s study has confirmed that UBB may be involved in hypoxia-induced cardiac remodeling[20]. Therefore, we speculated that UBB is most likely to be related to BTBD7_hsa_circ_0000563 and cardiovascular diseases among these 7 proteins.

Western blot was used to investigate the relationship between UBB and BTBD7_hsa_circ_0000563. Obvious accumulation of polyubiquitinated proteins was found in PBMCs of the control group (P = 0.007, Fig. 5), implying that UBB (polyubiquitin-B) was positively proportional to BTBD7_hsa_circ_0000563 at a post-transcriptional level.

Fig. 5

Validation of UBB (polyubiquitin-B) expression levels via western blot (A) The representative western blot image. (B) The statistical result of grayscale values (**: P < 0.01). The entire lane of each sample was used to determine the grayscale values. CAD, coronary artery disease; UBB, polyubiquitin-B

The clinical characteristics of subjects undergoing western blot are shown in Table S2, Additional file 2.