Dataset Information

A System-Wide Investigation and Stratification of the Hemostatic Proteome in Premature Myocardial Infarction

ABSTRACT:

Introduction

Advancing understanding of key factors that determine the magnitude of the hemostatic response may facilitate the identification of individuals at risk of generating an occlusive thrombus as a result of an atherothrombotic event such as an acute Myocardial Infarction (MI). While fibrinogen levels are a recognized risk factor for MI, the association of thrombotic risk with other coagulation proteins is inconsistent. This is likely due to the complex balance of pro- and anticoagulant factors in any individual.

Methods

We compared measured levels of pro- and anticoagulant proteins in plasma from 162 patients who suffered an MI at an early age (MI <50 y) and 186 age- and gender-matched healthy controls with no history of CAD. We then used the measurements from these individuals as inputs for an established mathematical model to investigate how small variations in hemostatic factors affect the overall amplitude of the hemostatic response and to identify differential key drivers of the hemostatic response in male and female patients and controls.

Results

Plasma from the MI patients contained significantly higher levels of Tissue Factor (P = 0.007), the components of the tenase (FIX and FVIII; P < 0.0001 for both) and the prothrombinase complexes (FX; P = 0.003), and lower levels of Tissue Factor Pathway Inhibitor (TFPI; P = 0.033) than controls. The mathematical model, which generates time-dependent predictions describing the depletion, activation, and interaction of the main procoagulant factors and inhibitors, identified different patterns of hemostatic response between MI patients and controls, and additionally, between males and females. Whereas, in males, TF, FVIII, FIX, and the inhibitor TFPI contribute to the differences seen between case and controls, and in females, FII, FVIII, and FIX had the greatest influence on the generation of thrombin. We additionally show that further donor stratification may be possible according to the predicted donor response to anticoagulant therapy.

Conclusions

We suggest that modeling could be of value in enhancing our prediction of risk of premature MI, recurrent risk, and therapeutic efficacy.

SUBMITTER: Dunster J

PROVIDER: S-EPMC9281867 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundSeveral biomarkers have individually been shown to be useful for risk stratification in patients with acute myocardial infarction (MI). The optimal multimarker strategy remains undefined.Methods and resultsBiomarkers representing different pathobiological axes were studied, including myocardial stress/structural changes (NT-pro B-type natriuretic peptide [NT-proBNP], midregional proatrial natriuretic peptide [MR-proANP], suppression of tumorigenicity 2 [ST2], galectin-3, midregional proadrenomedullin [MR-proADM], and copeptin), myonecrosis (troponin T), and inflammation (myeloperoxidase [MPO], high sensitivity C-reactive protein [hsCRP], pregnancy-associated plasma protein A [PAPP-A], and growth-differentiation factor-15 [GDF-15]), in up to 1258 patients from Clopidogrel as Adjunctive Reperfusion Therapy-Thrombolysis in Myocardial Infarction 28 (CLARITY-TIMI 28), a randomized trial of clopidogrel in ST-elevation MI (STEMI). Patients were followed for 30 days. Biomarker analyses were adjusted for traditional clinical variables. Forward step-wise selection was used to assess a multimarker strategy. After adjustment for clinical variables and using a dichotomous cutpoint, 7 biomarkers were each significantly associated with a higher odds of cardiovascular death or heart failure (HF) through 30 days, including NT-proBNP (adjusted odds ratio [ORadj], 2.54; 95% CI, 1.47-4.37), MR-proANP (2.18; 1.27-3.76), ST2 (2.88; 1.72-4.81), troponin T (4.13; 1.85-9.20), MPO (2.75; 1.20-6.27), hsCRP (1.96, 1.17-3.30), and PAPP-A (3.04; 1.17-7.88). In a multimarker model, 3 biomarkers emerged as significant and complementary predictors of cardiovascular death or HF: ST2 (ORadj, 2.87; 1.61-5.12), troponin T (2.34; 1.09-5.01 and 4.13, 1.85-9.20, respectively for intermediate and high levels), and MPO (2.49; 1.04-5.96). When added to the TIMI STEMI Risk Score alone, the multimarker risk score significantly improved the C-statistic (area under the curve, 0.75 [95% CI, 0.69-0.81] to 0.82 [0.78-0.87]; P=0.001), net reclassification index (0.93; P<0.001), and integrated discrimination index (0.09; P<0.001).ConclusionsIn patients with STEMI, a multimarker strategy that combines biomarkers across pathobiological axes of myocardial stress, myocyte necrosis, and inflammation provides incremental prognostic information for prediction of cardiovascular death or HF.