Sources of variability in quantifying circulating thymosin beta-4: literature review and recommendations

<p><b>Introduction</b>: Thymosin beta-4 (TB4) is an endogenous peptide with protective and regenerative effects in models of cellular and organ injury. TB4 is increasingly measured as a potential plasma or serum biomarker in human cardiovascular, liver, infectious, and autoimmune disease.</p> <p><b>Areas covered</b>: The focus of this review is the quantification of TB4 in clinical cohort studies and whether reported TB4 concentrations differ with respect to method of sample preparation. We survey current literature for studies measuring TB4 in human serum or plasma and compare reported concentrations in healthy controls.</p> <p><b>Expert opinion</b>: We find substantial intra- and inter- study variability in healthy controls, and a lack of protocol standardization. We further highlight three factors that may confound TB4 clinical measurements and should be considered in future study design: 1) residual platelets remaining in suspension after centrifugation, 2) TB4 release following <i>ex vivo</i> platelet activation, and 3) specificity of assays towards posttranslational modifications. Accordingly, we put forth our recommendations to minimize residual and activated platelets during sample collection, and to cross-validate TB4 measurements using both antibody-based and mass spectrometry-based methods.</p

Table_1_Plasma tissue factor coagulation activity in post-acute myocardial infarction patients.docx

IntroductionCoagulation is involved in fibroproliferative responses following acute myocardial infarction (AMI). Left ventricular (LV) remodeling following AMI is closely associated with progression to heart failure. This study aims to assess the association between plasma tissue factor activity and LV remodeling in post-AMI patients.MethodsWe studied 228 patients with AMI and 57 healthy subjects. Patients with AMI were categorized into two age- and sex-matched groups: patients with adverse LV remodeling or reverse LV remodeling, defined by an increase or decrease, respectively, in LV end systolic volume by ≥15% over 6 months. TF activity was measured in plasma collected at baseline (within 72 hours of revascularization), 1 month and 6 months post-AMI. Multiple level longitudinal data analysis with structural equation (ML-SEM) model was used to assess the impact of various clinical variables on TF activity in post-AMI.ResultsPlasma TF activity in post-AMI patients at baseline (29.05 ± 10.75 pM) was similar to that in healthy subjects but fell at 1 month (21.78 ± 8.23, pConclusionsPlasma TF activity decreased after AMI but was better restored at 6 months in patients with reverse LV remodeling. The clinical significance of changes in post-AMI plasma TF activity needs further investigation.</p

Datasheet2_An integrated signature of extracellular matrix proteins and a diastolic function imaging parameter predicts post-MI long-term outcomes.xlsx

BackgroundPatients suffering from acute myocardial infarction (AMI) are at risk of secondary outcomes including major adverse cardiovascular events (MACE) and heart failure (HF). Comprehensive molecular phenotyping and cardiac imaging during the post-discharge time window may provide cues for risk stratification for the outcomes.Materials and methodsIn a prospective AMI cohort in New Zealand (N = 464), we measured plasma proteins and lipids 30 days after hospital discharge and inferred a unified partial correlation network with echocardiographic variables and established clinical biomarkers (creatinine, c-reactive protein, cardiac troponin I and natriuretic peptides). Using a network-based data integration approach (iOmicsPASS+), we identified predictive signatures of long-term secondary outcomes based on plasma protein, lipid, imaging markers and clinical biomarkers and assessed the prognostic potential in an independent cohort from Singapore (N = 190).ResultsThe post-discharge levels of plasma proteins and lipids showed strong correlations within each molecular type, reflecting concerted homeostatic regulation after primary MI events. However, the two molecular types were largely independent with distinct correlation structures with established prognostic imaging parameters and clinical biomarkers. To deal with massively correlated predictive features, we used iOmicsPASS + to identify subnetwork signatures of 211 and 189 data features (nodes) predictive of MACE and HF events, respectively (160 overlapping). The predictive features were primarily imaging parameters, including left ventricular and atrial parameters, tissue Doppler parameters, and proteins involved in extracellular matrix (ECM) organization, cell differentiation, chemotaxis, and inflammation. The network signatures contained plasma protein pairs with area-under-the-curve (AUC) values up to 0.74 for HF prediction in the validation cohort, but the pair of NT-proBNP and fibulin-3 (EFEMP1) was the best predictor (AUC = 0.80). This suggests that there were a handful of plasma proteins with mechanistic and functional roles in predisposing patients to the secondary outcomes, although they may be weaker prognostic markers than natriuretic peptides individually. Among those, the diastolic function parameter (E/e' - an indicator of left ventricular filling pressure) and two ECM proteins, EFEMP1 and follistatin-like 3 (FSTL3) showed comparable performance to NT-proBNP and outperformed left ventricular measures as benchmark prognostic factors for post-MI HF.ConclusionPost-discharge levels of E/e', EFEMP1 and FSTL3 are promising complementary markers of secondary adverse outcomes in AMI patients.</p

Datasheet1_An integrated signature of extracellular matrix proteins and a diastolic function imaging parameter predicts post-MI long-term outcomes.pdf

BackgroundPatients suffering from acute myocardial infarction (AMI) are at risk of secondary outcomes including major adverse cardiovascular events (MACE) and heart failure (HF). Comprehensive molecular phenotyping and cardiac imaging during the post-discharge time window may provide cues for risk stratification for the outcomes.Materials and methodsIn a prospective AMI cohort in New Zealand (N = 464), we measured plasma proteins and lipids 30 days after hospital discharge and inferred a unified partial correlation network with echocardiographic variables and established clinical biomarkers (creatinine, c-reactive protein, cardiac troponin I and natriuretic peptides). Using a network-based data integration approach (iOmicsPASS+), we identified predictive signatures of long-term secondary outcomes based on plasma protein, lipid, imaging markers and clinical biomarkers and assessed the prognostic potential in an independent cohort from Singapore (N = 190).ResultsThe post-discharge levels of plasma proteins and lipids showed strong correlations within each molecular type, reflecting concerted homeostatic regulation after primary MI events. However, the two molecular types were largely independent with distinct correlation structures with established prognostic imaging parameters and clinical biomarkers. To deal with massively correlated predictive features, we used iOmicsPASS + to identify subnetwork signatures of 211 and 189 data features (nodes) predictive of MACE and HF events, respectively (160 overlapping). The predictive features were primarily imaging parameters, including left ventricular and atrial parameters, tissue Doppler parameters, and proteins involved in extracellular matrix (ECM) organization, cell differentiation, chemotaxis, and inflammation. The network signatures contained plasma protein pairs with area-under-the-curve (AUC) values up to 0.74 for HF prediction in the validation cohort, but the pair of NT-proBNP and fibulin-3 (EFEMP1) was the best predictor (AUC = 0.80). This suggests that there were a handful of plasma proteins with mechanistic and functional roles in predisposing patients to the secondary outcomes, although they may be weaker prognostic markers than natriuretic peptides individually. Among those, the diastolic function parameter (E/e' - an indicator of left ventricular filling pressure) and two ECM proteins, EFEMP1 and follistatin-like 3 (FSTL3) showed comparable performance to NT-proBNP and outperformed left ventricular measures as benchmark prognostic factors for post-MI HF.ConclusionPost-discharge levels of E/e', EFEMP1 and FSTL3 are promising complementary markers of secondary adverse outcomes in AMI patients.</p