Carotid artery color Doppler ultrasonography and plasma levels of lipoprotein-associated phospholipase A2 and cystatin C in arteriosclerotic cerebral infarction

Emerging Circulating Biomarkers for Enhanced Cardiovascular Risk Prediction

Cardiovascular disease (CVD) continues to be the primary cause of mortality worldwide, underscoring the importance of identifying additional cardiovascular risk factors. The consensus is that lipid levels alone do not fully reflect the status of atherosclerosis, thus necessitating extensive research on cardiovascular biomarkers. This review encompasses a wide spectrum of methodologies for identifying novel risk factors or biomarkers for CVD. Inflammation, oxidative stress, plaque instability, cardiac remodeling, and fibrosis play pivotal roles in CVD pathogenesis. We introduce and discuss several promising biomarkers-namely, osteocalcin, angiogenin, lipoprotein-associated phospholipase A2, growth differentiation factor 15, galectin-3, growth stimulation expressed gene 2, and microRNAs, all of which have potential implications in the assessment and management of cardiovascular risk.

Association of Lipoprotein-associated phospholipase A2 With Carotid Intima-Media Thickness in Acute Cerebral Infarction Patients

Lipoprotein-associated phospholipase A2 (Lp-PLA2) is an inflammatory marker associated with atherosclerotic and cardiovascular diseases. This study aimed to explore the association of Lp-PLA2 with carotid intima-media thickness (cIMT) in patients with acute ischemic stroke (AIS) and explore a threshold level to predict the risk of vulnerable plaques. This retrospective observational study included patients with AIS in the Neurology Department of our Hospital between January 2018 and December 2019. The study included 293 patients aged 65.29 ± 12.11 years, including 212 males, of whom 124 had carotid intima-media thickening (42.32%). Multivariable logistic regression showed that Lp-PLA2 level was an independent risk factor for cIMT (odds ratio [OR] = 1.004, 95% confidence interval [95% CI] 1.001-1.008, P = .008). Threshold effect analysis showed that the risk of vulnerable carotid plaque occurrence increased by 2% for every 1 ng/mL increase in Lp-PLA2 level with serum Lp-PLA2 levels between 157 and 279 ng/mL; this increase was statistically significant (OR = 1.02, 95% CI 1.01-1.03, P < .001). Serum Lp-PLA2 is an independent risk factor for increased cIMT in patients with AIS, and a threshold Lp-PLA2 level between 157 and 279 ng/mL showed a higher risk of carotid plaque rupture.

A retrospective study of immunoglobulin E as a biomarker for the diagnosis of acute ischemic stroke with carotid atherosclerotic plaques

Objective

In this study, serum markers of acute ischemic stroke (AICS) with carotid artery plaque were retrospectively evaluated to establish a basis for discovering serological indicators for early warning of acute ischemic stroke (AICS).

Methods

A total of 248 patients with AICS were enrolled in Lanzhou University Second Hospital from January 2019 to December 2020. The study population included 136 males and 112 females, 64 ± 11 years of age. Of these, there were 90 patients with a transient ischemic attack (TIA), including 60 males and 30 females, aged 64 ± 8 years old. Patients with AICS were stratified by carotid ultrasound into a plaque group (n = 154) and a non-plaque group (n = 94). A total of 160 healthy subjects were selected as the control group. Serum lipoprotein-associated phospholipase A2 (Lp-PLA2), amyloid A (SAA), immunoglobulin E (IgE), D-dimer (D-D), total cholesterol (TC), triglyceride (TG), and low-density lipoprotein cholesterol (LDL-C) were collected from all subjects. Multivariate logistic regression was used to analyze the risk factors of AICS with carotid plaque. ROC curve was used to analyze the diagnostic efficacy of AICS with carotid plaque.

Results

The IgE, Lp-PLA2, SAA, LDL-C, TC, TG, and D-D levels in the AICS group were higher than those in the TIA group and healthy control group (P < 0.05). The IgE level was significantly higher than that in the healthy control group and TIA group. The IgE level in the AICS plaque group was significantly higher than that in the AICS non-plaque group (P < 0.01), and the Lp-PLA2 level was also different (P < 0.05). The incidence of AICS was positively correlated with Lp-PLA2, TC, IgE, TG, D-D, SAA and LDL-C (r = 0.611, 0.499, 0.478, 0.431, 0.386, 0.332, 0.280, all P < 0.05). The incidence of AICS with plaque was only positively correlated with IgE and Lp-PLA2 (r = 0.588, 0.246, P < 0.05). Logistic regression analysis showed that IgE and Lp-PLA2 were independent risk factors for predicting the occurrence of AICS with carotid plaque (P < 0.05). ROC curve analysis showed that the AUC of IgE (0.849) was significantly higher than other indicators; its sensitivity and specificity were also the highest, indicating that IgE can improve the diagnostic efficiency of AICS with carotid plaque.

Conclusion

IgE is a serum laboratory indicator used to diagnose AICS disease with carotid plaque, which lays a foundation for further research on potential early warning indicators of AICS disease.

Recognized and Potentially New Biomarkers-Their Role in Diagnosis and Prognosis of Cardiovascular Disease

Atherosclerosis and its consequences are the leading cause of mortality in the world. For this reason, we have reviewed atherosclerosis biomarkers and selected the most promising ones for review. We focused mainly on biomarkers related to inflammation and oxidative stress, such as the highly sensitive C-reactive protein (hs-CRP), interleukin 6 (IL-6), and lipoprotein-associated phospholipase A2 (Lp-PLA2). The microRNA (miRNA) and the usefulness of the bone mineralization, glucose, and lipid metabolism marker osteocalcin (OC) were also reviewed. The last biomarker we considered was angiogenin (ANG). Our review shows that due to the multifactorial nature of atherosclerosis, no single marker is known so far, the determination of which would unambiguously assess the severity of atherosclerosis and help without any doubt in the prognosis of cardiovascular risk.

The clinical value of blood flow parameters of the umbilical artery and middle cerebral artery for assessing fetal distress

OBJECTIVE

To explore the clinical value of blood flow parameters of the umbilical artery (UA) and middle cerebral artery (MCA) for gauging fetal distress.

METHODS

This study was conducted among 256 pregnant women who presented for routine prenatal checkups and successfully gave birth in our hospital from January 2018 to February 2020. These pregnant women were examined with the Color Doppler Ultrasound, and the color Doppler flow imaging (CDFI) showed the blood flow of the UA and MCA. In accordance with the diagnostic criteria of fetal distress, they were divided into a fetal distress group (n=67) and a control group (n=189). The receiver operator characteristic (ROC) curve analysis was performed on the diagnostic value of the flow in the UA and MCA. According to their pregnancy outcomes, they were divided into a good pregnancy outcome group (n=209) and an adverse pregnancy outcome group (n=47), and their blood flow parameters of the UA and MCA were compared.

RESULTS

The S/D, PI, and RI values of the UA in the fetal distress group exceeded those in the control group, and the S/D, PI, and RI values of the MCA were lower than those in the control group (P<0.05). The good pregnancy outcome group had lower S/D, PI, and RI values of the UA. The good pregnancy outcome group had higher S/D, PI, and RI values of the MCA (P<0.05). ROC curves revealed that the areas under curve of S/D, PI, and RI of the UA were 0.81, 0.76 and 0.74, respectively; the areas under curve of S/D, PI, and RI of the MCA were 0.82, 0.78 and 0.71, respectively.

CONCLUSION

The hemodynamic indexes of the UA and MCA can be used as a basis for evaluating fetal distress, which shows important clinical indications for gauging pregnancy outcome.

Association of neuroimaging markers of cerebral small vessel disease with short-term outcomes in patients with minor cerebrovascular events

Background

Increasing evidences have showed that neuroimaging markers of SVD can predict the short-term outcome of acute ischemic stroke (AIS). It is unclear that whether neuroimaging markers of SVD are also associated with short-term outcomes of minor cerebrovascular events. In the present study, we investigate neuroimaging markers of SVD in order to explore their roles in prediction of short-term outcome in patients with minor cerebrovascular events.

Methods

Consecutive first-ever stroke patients (n = 546) from the Affiliated Jiangning Hospital of Nanjing Medical University were enrolled. A total of 388 patients were enrolled according to minor cerebrovascular events definition (National Institutes of Health Stroke Scale Score ≤ 3) and exclusion criteria. MRI scans were performed within 7 days of stroke onset, and then neuroimaging markers of SVD including WMH, lacunes, cerebral microbleeds (CMB), and perivascular spaces (PVS), SVD burden scores were assessed. We completed baseline characteristics and evaluated the relationships of short-term outcomes to SVD neuroimaging markers and SVD scores. The 90-day modified Rankin Scale (mRS) was thought as primary outcome and was dichotomized as good functional outcome (mRS 0–1) and poor outcome (mRS 2–6). Secondary outcomes were stroke progression and stroke recurrence.

Results

Higher age, National Institutes of Health Stroke Scale (NIHSS) upon admission, lipoprotein-associated phospholipase A2 (LP-PLA2) and lacunes, Fazekas score were correlated with poor functional outcome (P < 0.05), But after adjusting for confounding variables, among the neuroimaging markers of cerebral small vessel disease, only Fazekas score (OR, 1.343; 95% confidence interval, 1.020–1.770; P = 0.036) was found to be associated with poor outcome at 90 days. Higher Fazekas and SVD scores were not associated with stroke progression or stroke recurrence.

Conclusion

WMH can predict the poor functional outcome of minor cerebrovascular events. Adding other neuroimaging markers of SVD and total SVD burden score, however, does not improve the prediction, which indicated WMH can as neuroimaging markers for guiding the treatment of minor cerebrovascular events.

An analysis of the correlation between the human apolipoprotein E gene polymorphism and lipoprotein-associated phospholipase A2

Background

Atherosclerosis is one of the most common cardiovascular and cerebrovascular diseases. This study aimed to explore the correlation between gene polymorphism of human apolipoprotein E (ApoE) and lipoprotein-associated phospholipase A2 (Lp-PLA2).

Methods

A total of 220 patients with atherosclerotic cardiovascular disease who were treated in our hospital from June 2016 to March 2017 were enrolled in this study and assigned as the atherosclerotic cardiovascular disease group and 193 patients who were treated contemporaneously in our hospital but had no atherosclerotic cardiovascular disease were enrolled and assigned as the control group. Gene polymorphism of ApoE was detected by PCR-fluorescent probe technique and the level of Lp-PLA2 was detected by ELISA.

Results

There were a total of 5 genotypes of ApoE in these two groups, which were E2/3, E3/3, E3/4, E2/4, and E4/4. E2/2 was not found in any of the patients. E3/3 made up the majority in both groups. There was no significant difference between the proportion of genotypes and frequencies of alleles in the two groups (P>0.05). There was no difference between LP-PLA2 among the different genotypes in these two groups (P>0.05).

Conclusions

We cannot conclude that ApoE gene polymorphism is related to atherosclerotic cardiovascular and cerebrovascular diseases. And it cannot be concluded that ApoE gene polymorphism is related to Lp-PLA2 level.

Untargeted metabolomics predicts the functional outcome of ischemic stroke

BACKGROUND/PURPOSE

Metabolites in blood have been found associated with the occurrence of vascular diseases, but its role in the functional recovery of stroke is unclear. The aim of this study is to investigate whether the untargeted metabolomics at the acute stage of ischemic stroke is able to predict functional recovery.

METHODS

One hundred and fifty patients with acute ischemic stroke were recruited and followed up for 3 months. Fasting blood samples within 7 days of stroke were obtained, liquid chromatography and mass spectrometry were applied to identify outcome-associated metabolites. The patients' clinical characteristics and identified metabolites were included for constructing the outcome prediction model using machine learning approaches.

RESULTS

By using multivariate analysis, 220 differentially expressed metabolites (DEMs) were discovered between patients with favorable outcomes (modified Rankin Scale, mRS ≤ 2 at 3 months, n = 77) and unfavorable outcomes (mRS ≥ 3 at 3 months, n = 73). After feature selection, 63 DEMs were chosen for constructing the outcome prediction model. The predictive accuracy was below 0.65 when including patients' clinical characteristics, and could reach 0.80 when including patients' clinical characteristics and 63 selected DEMs. The functional enrichment analysis identified platelet activating factor (PAF) as the strongest outcome-associated metabolite, which involved in proinflammatory mediators release, arachidonic acid metabolism, eosinophil degranulation, and production of reactive oxygen species.

CONCLUSION

Metabolomics is a potential method to explore the blood biomarkers of acute ischemic stroke. The patients with unfavorable outcomes had a lower PAF level compared to those with favorable outcomes.