Clin Res Cardiol (2022).

Identification of specific coronary artery disease phenotypes implicating differential pathophysiologies
J. B. Krohn1, Y. N. Nguyen1, M. Akhavanpoor2, C. Erbel1, G. Domschke1, F. A. Linden1, M. Kleber3, G. Delgado3, W. März4, H. A. Katus1, C. A. Gleißner2
1Klinik für Innere Med. III, Kardiologie, Angiologie u. Pneumologie, Universitätsklinikum Heidelberg, Heidelberg; 2Innere Medizin 2, Rottal-Inn-Kliniken Eggenfelden, Eggenfelden; 3Med V. - Nephrologie, Endokrinologie und Rheumatologie, Universitätsklinikum Mannheim, Mannheim; 4SYNLAB Akademie, SYNLAB Holding Deutschland GmbH, Mannheim;
Background and Aims: The roles of multiple risk factors of coronary artery disease (CAD) such as arterial hypertension or increased LDL-cholesterol are well established. Commonly, CAD is considered as a single disease entity. We wish to examine whether coronary angiography allows to identify distinct CAD phenotypes with specific spatial distribution of critical coronary stenoses and their potential association with major risk factors and differences in prognosis. 
Methods: In a cohort of 4,344 patients undergoing coronary angiography at Heidelberg University Hospital between 2014 and 2016, cluster analysis of angiographic reports identified subgroups with similar CAD morphology. Clusters were independently confirmed in 3,129 patients from the LURIC study. Cluster affiliation as a prognostic risk factor was investigated using logistic regression.
Results: Four clusters were identified: cluster one lacking critical stenoses comprised the highest percentage of women with the lowest cardiovascular risk. Patients in cluster two exhibiting high-grade stenosis of the proximal RCA had a high prevalence of the metabolic syndrome, and, showed the highest levels of inflammatory biomarkers. Cluster three with predominant proximal LAD stenosis frequently presented with acute coronary syndrome and elevated troponin levels. Cluster four with high-grade stenoses throughout had the oldest patients with the highest overall cardiovascular risk. All-cause and cardiovascular mortality differed significantly between the clusters.
Conclusions: Cluster analysis of coronary angiography reports of >7000 patients at two different centers identified four phenotypic subgroups of CAD bearing distinct demographic and biochemical characteristics as well as differences in prognosis independent of established cardiovascular risk factors. These results may point at the existence of multiple disease entities currently summarized as coronary artery disease, a finding that warrants further investigation.