Abstract:Aims Autotaxin (ATX) promotes myocardial inflammation, fibrosis, and the subsequent cardiac remodelling through lysophosphatidic acid production. However, the prognostic impact of serum ATX in non-ischaemic dilated cardiomyopathy (NIDCM) has not been clarified. We investigated the prognostic impact of serum ATX in patients with NIDCM.
Methods and resultsWe enrolled 104 patients with NIDCM (49.8 ± 13.4 years, 76 men). We divided the patients into two groups using different cutoffs of median serum ATX levels for… Show more
“…Recent studies have also con rmed that Autotaxin can mediate in ammation and brosis through LysoPA, leading to organ remodeling. By inhibiting ATX, the level of LysoPA was signi cantly reduced, and inhibition of myocardial brosis was accompanied by inhibition of myocardial structural remodeling as well as increased cardiac dysfunction [30]. In ammation and myocardial brosis were important pathophysiological features of dilated cardiomyopathy, and our results also show that DCM patients are accompanied by higher levels of LysoPA.…”
(1) Objects: Our aim was to identify changes in the metabolome in dilated cardiomyopathy (DCM) as well as to construct a metabolic diagnostic model for DCM.
(2) Methods: We utilized non-targeted metabolomics with a cross-sectional cohort of age- and sex-matched DCM patients and controls. Metabolomics data were analyzed using orthogonal partial least squares-discriminant analysis (OPLS-DA) and pathway analysis. It was validated in combination with transcriptome sequencing data from public databases. Machine learning models were used for the diagnosis of DCM.
(3) Results: Using multiple analytical techniques, 130 metabolite alterations were identified in DCM compared to healthy controls. Perturbations in glycerophospholipid metabolism (GPL) were identified and validated as a characteristic metabolic pathway in DCM. Through the least absolute shrinkage and selection operator (LASSO), we identified the 7 most important GPL metabolites, including LysoPA (16:0/0:0), LysoPA (18:1(9Z)/0:0), PC (20:3(8Z,11Z,14Z)/20:1(11Z)), PC (20:0/14:0), LysoPC (16:0), PS(15:0/18:0), and PE(16:0/20:4 (5Z,8Z,11Z,14Z)). The machine learning models based on the seven metabolites all had good accuracy in distinguishing DCM [All area under the curve (AUC) >0.900], and the artificial neural network (ANN) model performed the most consistently (AUC: 0.919±0.075).
(4) Conclusions: This study demonstrates that GPL metabolism may play a contributing role in the pathophysiological mechanisms of DCM. The 7-GPL metabolite model may help for early diagnosis of DCM.
“…Recent studies have also con rmed that Autotaxin can mediate in ammation and brosis through LysoPA, leading to organ remodeling. By inhibiting ATX, the level of LysoPA was signi cantly reduced, and inhibition of myocardial brosis was accompanied by inhibition of myocardial structural remodeling as well as increased cardiac dysfunction [30]. In ammation and myocardial brosis were important pathophysiological features of dilated cardiomyopathy, and our results also show that DCM patients are accompanied by higher levels of LysoPA.…”
(1) Objects: Our aim was to identify changes in the metabolome in dilated cardiomyopathy (DCM) as well as to construct a metabolic diagnostic model for DCM.
(2) Methods: We utilized non-targeted metabolomics with a cross-sectional cohort of age- and sex-matched DCM patients and controls. Metabolomics data were analyzed using orthogonal partial least squares-discriminant analysis (OPLS-DA) and pathway analysis. It was validated in combination with transcriptome sequencing data from public databases. Machine learning models were used for the diagnosis of DCM.
(3) Results: Using multiple analytical techniques, 130 metabolite alterations were identified in DCM compared to healthy controls. Perturbations in glycerophospholipid metabolism (GPL) were identified and validated as a characteristic metabolic pathway in DCM. Through the least absolute shrinkage and selection operator (LASSO), we identified the 7 most important GPL metabolites, including LysoPA (16:0/0:0), LysoPA (18:1(9Z)/0:0), PC (20:3(8Z,11Z,14Z)/20:1(11Z)), PC (20:0/14:0), LysoPC (16:0), PS(15:0/18:0), and PE(16:0/20:4 (5Z,8Z,11Z,14Z)). The machine learning models based on the seven metabolites all had good accuracy in distinguishing DCM [All area under the curve (AUC) >0.900], and the artificial neural network (ANN) model performed the most consistently (AUC: 0.919±0.075).
(4) Conclusions: This study demonstrates that GPL metabolism may play a contributing role in the pathophysiological mechanisms of DCM. The 7-GPL metabolite model may help for early diagnosis of DCM.
Aims Autotaxin (ATX) promotes myocardial inflammation, fibrosis, and the subsequent cardiac remodelling through lysophosphatidic acid production. However, the prognostic impact of serum ATX in non-ischaemic dilated cardiomyopathy (NIDCM) has not been clarified. We investigated the prognostic impact of serum ATX in patients with NIDCM.
Methods and resultsWe enrolled 104 patients with NIDCM (49.8 ± 13.4 years, 76 men). We divided the patients into two groups using different cutoffs of median serum ATX levels for men and women: high-ATX group and low-ATX group. Cardiac events were defined as a composite of cardiac death and heart failure resulting in hospitalization. Median ATX level was 203.5 ng/mL for men and 257.0 ng/mL for women. Brain natriuretic peptide levels [224.0 (59.6-689.5) pg/mL vs. 96.5 (40.8-191.5) pg/mL, P = 0.010] were higher in the high-ATX group than low-ATX group, whereas high-sensitivity C-reactive protein and collagen volume fraction levels in endomyocardial biopsy samples were not significantly different between the two groups. Kaplan-Meier survival analysis revealed that the event-free survival rate was significantly lower in the high-ATX group than low-ATX group (log-rank; P = 0.007). Cox proportional hazard analysis revealed that high-ATX was an independent determinant of composite cardiac events. In both sexes, serum ATX levels did not correlate with high-sensitivity C-reactive protein levels and collagen volume fraction but had a weak correlation with brain natriuretic peptide levels (men; spearman's rank: 0.274, P = 0.017, women; spearman's rank: 0.378, P = 0.048). Conclusion High serum ATX levels can be associated with increasing adverse clinical outcomes in patients with NIDCM. These results indicate serum ATX may be a novel biomarker or therapeutic target in NIDCM.
Cardiovascular thromboembolic diseases and cancer continue to be a leading cause of death and disability worldwide. Therefore, it is crucial to advance their diagnoses and treatment in the context of individualized medicine. However, the disease specificity of the currently available markers is limited. Based on analyses of a subset of peptides and matching proteins in disease vs. healthy platelets, scientists have recently shown that focused platelet proteomics enables the quantification of disease-specific biomarkers in humans. In this review, we explored the potential of accurate platelet proteomic research, which is required to identify novel diagnostic and pharmaceutical targets by comprehending the proteome variety of healthy individuals and patients for personalized and precision medicine.
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