Coronary inflammatory marker helps identify hidden cardiac risk in young adults

Coronary inflammatory marker helps identify hidden cardiac risk in young adults

A new study shows that measuring coronary inflammation with PCAT can detect early heart disease in young adults, even when standard calcium scans show nothing. This breakthrough could change the way we identify and treat hidden cardiovascular risk.

In a recently published study in theAmerican Journal of Prudemitive CardiologyResearchers examined the relationship between peri-coronary adipose tissue deficiency (PCAT) and coronary artery disease (CAD) in young people.

Cardiovascular disease (CVD) is the leading cause of death worldwide, with a growing incidence among young adults despite a reduction in CVD mortality. Early detection of atherosclerosis in young people is critical because conventional risk models often underestimate risk in this population. Calonary artery calcium (CAC) screening and coronary computed tomography angiography (CCTA) are robust tools for detecting early coronary artery disease (CAD).

PCAT is a coronary inflammatory marker and plays a crucial role in early atherogenesis. It correlates with the presence and severity of CAD. Identification of premature atherosclerosis by CCTA or CAC assessment may lead to earlier initiation of prophylactic therapy in individuals who are not otherwise qualified based on traditional risk assessment. Therefore, PCAT can serve as an additional biomarker to improve risk stratification.

About the study

In the present study, researchers examined the interaction between PCAT and CAD in a young cohort. Symptomatic adults aged 18 to 45 years who underwent CCTA for suspected CAD between June 2016 and December 2022 were identified from the Montefiore CCTA registry. Clinical and demographic data were obtained from medical records. Cardiac imaging specialists reviewed all CCTA images. CAD was defined as the presence of visible plaque on CCTA or a CAD Report and Data System (CAD Wheel) ≥1.

Obstructive CAD was defined as stenosis ≥50% in any coronary artery. The Agatston method was used to estimate the CAC score. Furthermore, semi-automated software was used for quantitative plaque analysis in segments with a diameter of ≥ 2 mm. In subjects with coronary plaque, the volumes of invalid plaque (NCP), calcified plaque, total plaque, and low-oscillation plaque were quantified; In patients with CAD, the mean total plaque burden was 40.56% and the mean total plaque volume was 340.94 mm³.

PCAT was defined as tissue with -190 Hounsfield units (HU) to -30 Hu in a single concentric layer. The average PCAT for each coronary artery was calculated, and the total PCAT was derived as an average across three coronary vessels: left circumflex (LCX), right (RCA), and left anterior descending (LAD) coronary arteries. Logistic regression models examined the association between CAD and PCAT.

Restricted cubic spline regression analysis was used to evaluate the relationship between PCAT and CAD risk. Receiver operating characteristic curve (ROC) analysis evaluated the discriminative ability for CAD using two models; The primary model included established cardiovascular risk factors (hypertension, BMI, smoking, hyperlipidemia and diabetes) and the other additionally integrated total pCAT.

Results

The study included 733 patients with a median age of 37. Of these, 55% were female and the cohort included diverse ethnicities (44% Hispanic, 23% non-Hispanic black, 5.3% non-Hispanic white, 3.4% non-Hispanic Asian, and 25.1% unknown/other). About 15% of patients had evidence of CAD on CCTA. CAD patients had a higher prevalence of diabetes, hypertension, hyperlipidemia, family history of CAD, and lower high-density lipoprotein cholesterol (HDL-C) levels. Overall, 90.2% of the study population had a CAC score of 0; Of these, 34 had evidence of NCP.

In CAD patients, 13% had obstructive disease, 87% had non-obstructive disease, and 86.8% had mild stenosis. PCAT was -78.94 Hu overall, -77.3 Hu in the LCX, -80.14 Hu in the RCA, and -80.17 Hu in the LAD. Men had a higher LCX PCAT than women. CAD patients had higher total pCAT, LCX-PCAT, and RCA-PCAT than non-CAD subjects. Conversely, LAD PCAT was not significantly different between non-CAD and CAD patients.

PCAT was linearly associated with atherosclerosis as confirmed by restricted cubic spline regression analysis, with a stronger association observed with increasing PCAT values. PCAT values ​​above the specific cutoff values ​​(for each coronary artery using the Youden index and referred to as “High PCAT” in the study for analytical purposes) were independently associated with CAD, adjusting for sex, age, body mass index (BMI), hypertension, smoking, hyperlipidemia, and family CAD history. In patients with a CAC score of 0, CAD patients had significantly increased LCX-PCAT than non-CAD patients.

Additionally, there was an association between LCX PCAT and the presence of atherosclerosis, adjusting for hyperlipidemia, family CAD history, and sex. In ROC curve analysis, the primary model with traditional risk factors achieved moderate discriminative ability for coronary atherosclerosis. Incorporating the entire PCAT into the model, with the paper's discussion highlighting the specific contribution of LCX PCAT, significantly improved the predictive ability.

It is important to note that the authors acknowledged several limitations, including the retrospective nature of the study, selection lock as it included only symptomatic patients, the lack of long-term outcome data, and the need for further standardization of PCAT measurement techniques.

Conclusions

Overall, PCAT was increased in young, symptomatic CAD patients and was associated with the presence of CAD. PCAT was also independently associated with CAC in patients with a CAC score of 0. Overall, the results emphasize the predictive value of PCAT in a young population, suggesting its role as a novel non-invasive marker for the detection of CAD. Incorporating PCAT into clinical practice could improve risk stratification and identify those who may benefit from early intervention.

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