Serum free fatty acids are associated with severe coronary artery calcification, especially in diabetes: a retrospective study

This was a single-center, retrospective study conducted at the Shanghai Ninth People's Hospital affiliated with Shanghai Jiao Tong University School of Medicine from February 2017 to February 2020. The enrollment criteria were as follows: (1) patients aged ≥ 18 years, and (2) patients who underwent CAG and IVUS for a de novo lesion and were diagnosed with CAD. The exclusion criteria were as follows: (1) previous PCI or coronary artery bypass grafting (CABG) on the target vessel; (2) patients with a lesion of chronic total occlusion; (3) moderate or severe cardiac valve disease; (4) NYHA class 3–4 heart failure; (5) type 1 DM (T1DM); (6) patients with a declined renal function of eGFR ≤ 30 ml/min/1.73 m² or who underwent hemodialysis; (7) severe hepatic dysfunction; (8) malignant tumor; or (9) patients with poor quality IVUS imaging or lack of laboratory test results. All patients gave written informed consent, and the study protocol was approved by the Institution's Human Investigation Committee. Procedures were performed in accordance with the Declaration of Helsinki.

Detailed medical history of the patients was collected after hospitalization. Weight and height were recorded and body mass index (BMI) was calculated by weight/height² (kg/m²). Blood pressure was measured on admission. Blood samples were routinely collected in the morning after overnight fasting when hospitalized, including lipid profiles (serum FFA was part of the fasting lipid profiles), kidney function, HbA1c et al. Estimated glomerular filtration rate (eGFR) were calculated according to CKD-EPI equation.

The CAG procedures were performed according to generally accepted guidelines and routines [27, 28]. The radial artery was the preferred access approach. Lesions were imaged in at least two different projections, preferably at 90°. A lesion with a reduced luminal diameter of at least 50% was considered significant. All procedures were performed by two experienced interventional cardiologists, with sub-senior title or higher. Both the cardiologists decided together whether or not an IVUS procedure was needed after CAG. After intracoronary administration of 200 μg of nitroglycerin, pre-intervention IVUS imaging of all the coronaries was performed using a commercially available IVUS system and catheter (iLab™ Ultrasound Imaging System, Boston Scientific Corp. Natic, MA, USA; Opticross™ 3.0 F intracoronary ultrasound catheter, Boston Scientific). The IVUS catheter was placed at least 10 mm distal to the lesion and then moved backward automatically at a speed of 0.5 mm/s until it reached the coronary ostium.

All IVUS data were stored in DVDs and analyzed offline according to the criteria of the American College of Cardiology Clinical Expert Consensus Document on Standards for Acquisition, Measurement and Reporting of Intravascular Studies [29]. Analyses were independently performed with echo plaque software (Indec Medical Systems, Santa Clara, CA) by two experienced interventional cardiologists who were blinded to all the patients’ characteristics. From all the coronaries, we selected the vessel with the most severe lesion and the most severe calcified plaque as our targets. In the case of multiple lesions within a single coronary segment, distinct lesions or stenosis had at least 5 mm distance between them, with the most severe lesion as our target. The lesion length was measured. The reference sites were the most normal-appearing positions within 5 mm proximal and distal to the lesion border but before any side branch, and were used to calculate a mean reference cross-sectional area (CSA). The minimum lumen CSA sites were the slices with the smallest lumen CSA. Quantitative analysis included the measurement of the external elastic membrane (EEM) and lumen area (LA) in the minimum lumen area (MLA) position. Plaque plus media CSA was calculated as MLA-EEM minus MLA-LA. Plaque burden was calculated as plaque and media CSA divided by MLA-EEM multiplied by 100%.

Coronary calcium was defined as a brighter plaque than adventitia with acoustic shadowing. The arc of the calcified plaque in the lesion was measured. Calcium length was determined as the length of the calcified plaque with an arc. According to the arc value, the cohort was divided into two groups: (1) Patients with an arc ≥ 180° were classified into the SCAC group, and those with a calcified arc < 180° or no calcium were classified into the non-SCAC group.

Statistical analysis was performed with SPSS version 20.0 (IBM Corp., Armonk, NY, USA). Continuous variables are expressed as the Mean ± SD for normally distributed variables. Categorical data are presented as frequencies and proportions. Continuous variables were assessed using unpaired Student's t-tests, while categorical variables were compared using chi-square tests. Pearson’s correlation analyses between serum FFAs, and clinical and IVUS data were performed. Binary logistic regressions were used to calculate the correlations between the confounders and SCAC. Parameters were considered potential confounders if associations were found with a p-value < 0.10 in single factor analysis. Receiver operating characteristic (ROC) curves were constructed to assess the diagnostic value of FFAs according to the area under the curve (AUC). All p-values and confidence intervals (CI) were two-sided, and p < 0.05 was considered statistically significant.

Totally, 495 patients who underwent both CAG and IVUS were analyzed. A total of 69 patients were excluded, including 36 cases for previous PCI on target vessel, 2 for CABG of the target, 6 for severe heart failure, 1 for T1DM, 5 for declined renal function, 5 for cancer, 9 for insufficient lab results and 5 for poor quality IVUS. Finally, 426 vessels from 426 patients (SCAC group: 106, 24.9%) were included. Table 1 shows that patients in the SCAC group were older (71.74 ± 9.44 vs. 65.62 ± 10.11 years, p < 0.001), more likely to have a history of DM (37.7% vs. 26.2%, p = 0.024), elevated HbA1c (6.59 ± 1.48 vs. 6.26 ± 1.33, p = 0.031), increased pulse pressure (62.41 ± 15.07 vs. 54.55 ± 12.55 mmHg, p < 0.001) and decreased renal function (76.00 ± 20.56 vs. 82.51 ± 20.64 ml/min/1.73 m², p = 0.005). Serum FFA levels were significantly increased in the SCAC group (6.62 ± 2.17 vs. 5.13 ± 1.73 mmol/dl, p < 0.001). No significant differences in clinical presentation, serum cholesterol levels, total triglyceride levels, or use of drugs were observed between the two groups (Table 1).

The distribution of SCAC in the coronaries was similar to that in the non-SCAC group (Table 2). There were no significant differences in MLA-EEM and reference EEM between the two groups. Patients with SCAC tended to have a severe lesion with an increased lesion length (33.73 ± 13.25 vs. 18.91 ± 10.0 mm, p < 0.001), a smaller MLA-LA (3.82 ± 1.68 vs. 4.92 ± 2.79 mm², p < 0.001) and a higher plaque burden (0.73 ± 0.08 vs. 0.67 ± 0.11, p < 0.001) than the non-SCAC patients. Calcium length (11.36 ± 5.73 vs. 4.97 ± 3.44 mm, p < 0.001) and calcium arc (290.56 ± 62.91 vs. 90.03 ± 41.42°, p < 0.001) were also increased in the SCAC group (Table 2).

Pearson’s correlation analysis revealed that serum FFA levels were significantly correlated with plaque burden (r = 0.157, p = 0.001), lesion length (r = 0.224, p < 0.0001), calcium length (r = 0.173, p = 0.002), calcium arc (r = 0.353, p < 0.001) and HbA1c (r = 0.167, p < 0.001). No positive relationship was found between serum FFAs and BMI (r = 0.032, p = 0.505) (Fig. 1).

No positive correlations were found between subfractions of serum lipid profiles (triglyceride, total cholesterol, high density lipoprotein, low density lipoprotein) and calcium parameters (calcium arc, calcium length of arc), except for a weak correlation between high density lipoprotein and calcium length (r = 0.130, p = 0.023), (Fig. 2).

All the variables were compared with independent t-tests or chi-square test. Potential confounders with a p-value < 0.10 combined with traditionally recognized risk factors of cardiovascular disease were entered into the logistic regression model. We built three models as presented in Table 3 and Fig. 3. Model 1 showed that in the whole cohort, after adjusting for pulse pressure, age, eGFR and HbA1c, serum FFA levels were independently associated with SCAC (OR = 1.414, 95% CI = 1.237–1.617, p < 0.001, Model 1), with a 41.4% increased odds of SCAC for every 1 mmol/dl increase in serum FFA. Model 2 revealed that in the non-DM group (n = 302), the relationship was weakened (OR = 1.273, 95% CI = 1.087–1.492, p = 0.003, Model 2). As for the DM group (n = 124), the association was the strongest (OR = 1.939, 95% CI = 1.388–2.710, p < 0.001, Model 3), with a 93.9% increased odds of SCAC for every 1 mmol/dl increase in serum FFA after adjusting for traditional cardiovascular risk factors. Serum FFA levels in the DM group were higher compared with the non-DM group (Additional file 1: Table S1).

The predictive ability of serum FFAs for SCAC was assessed by ROC curve analysis (Fig. 4). Similar to the logistic regression results, the AUC was 0.695 (CI 0.641–0.750, p < 0.001, cutoff value: 5.0 mmol/dl; sensitivity: 79.3%; specificity: 51.6%) in the total population. In the non-DM group, the AUC was 0.649 (CI 0.580–0.718, p < 0.001, cutoff value: 5.0 mmol/dl; sensitivity: 71.2%; specificity: 53.0%). The AUC value (0.775) was the highest in the DM group (CI 0.690–0.859, p < 0.001, cutoff value: 5.3 mmol/dl; sensitivity: 87.5%; specificity: 53.6%).