メタボリックシンドロームの構成要素が血小板凝集を介してCOVID-19の転帰に影響を与える

Emerging evidence suggests that platelet activation and aggregation are common factors in both metabolic syndrome (MetS) and severe COVID-19, emphasizing the need to investigate their biological connection.

We hypothesized that enhanced platelet aggregation mediates the association between MetS and severe COVID-19. This study aimed to determine whether platelet aggregation serves as a mechanistic link between MetS and COVID-19 severity and to develop an image-based biomarker capable of predicting severe disease.

We conducted massive image-based profiling of circulating platelets in a retrospective cohort of 327 COVID-19 patients (63.9% male, median age 59.0 years) with metabolic records. Morphological features of platelets, including shape, density and radial distribution, and texture, were extracted. A machine-learning model was developed to construct the COVID-19 Platelet Aggregate Formation Index (CoPAFI), which quantitatively reflects platelet aggregation and predicts severe COVID-19. Mediation analysis was then performed to quantify the extent to which platelet aggregation mediated the association between components of MetS and severe COVID-19.

The CoPAFI predicted severe COVID-19 with an AUC of 0.82 and an odds ratio of 3.76 (95% CI, 2.63-5.38). The CoPAFI is strongly associated with a hypercoagulable state and serves as a reliable indicator for assessing the risk of severe COVID-19. In patients with components of MetS, platelet aggregation, as measured by the CoPAFI, accounts for approximately 25% of the increased severity of COVID-19.

Enhanced platelet aggregation partially mediates the impact of components of MetS on COVID-19 severity, accounting for approximately 25% of the association, emphasizing the need for integrated metabolic and coagulation management in COVID-19 treatment.