Residual cardiovascular risk of lipid origin. Components and pathophysiological aspects

Evaluation of Lipoprotein Profile and Residual Risk Three Years After Bariatric Surgery

INTRODUCTION

Obesity is a chronic disease associated with other comorbidities, including atherogenic dyslipidemia (AD). Bariatric surgery (BS) has shown to reduce cardiovascular risk (CVR) by achieving a significant weight reduction and improving the lipid profile. Different surgical techniques may have a different effect on the lipoprotein profile.

PURPOSE

To evaluate the lipid profile at 3 years after BS according to the surgical technique used and to determine which variables predict variation in the lipid profile at 3 years after BS.

METHODS

Retrospective observational study of 206 patients who underwent BS between 2010 and 2019. We analyzed the variation of lipid parameters in the 3 years of follow-up according to the surgical technique, including a group analysis of patients according to whether they had dyslipidemia and whether they were treated or untreated and determined which variables predict variation in the lipid profile at 3 years after BS.

RESULTS

There was a significant increase in high-density lipoprotein cholesterol (HDL-c) with sleeve gastrectomy (SG) and a significant decrease in total cholesterol (TC), LDL-cholesterol (LDL-c), non-HDL, and LDL/non-HDL with biliopancreatic diversion (BPD). Variables predicting lipid profile variation were surgical technique and pre-surgery lipoprotein level.

CONCLUSIONS

Malabsorptive techniques achieve a greater decrease in TC and LDL-c throughout follow-up and could also improve residual cardiovascular risk (non-HDL and LDL/non-HDL). The type of surgical technique and the presurgery lipid profile predict variation after 3 years of BS.

Serum lipoprotein(a) and risk of periprocedural myocardial injury in patients undergoing percutaneous coronary intervention

Recent studies and guidelines have indicated that lipoprotein(a) [Lp(a)]was an independent risk factor of arteriosclerotic cardiovascular disease (ASCVD). This study aimed to determine the relationship between serum Lp(a) levels and the risk of periprocedural myocardial injury following percutaneous coronary intervention (PCI) in coronary heartdisease (CHD) patients. This study enrolled 528 nonacute myocardial infarction (AMI) coronary heart disease (CHD) patients who successfully underwent PCI. Fasting serum lipids including Lp(a) were tested before PCI. High-sensitivity cardiac troponin I (hs-cTnI) was tested before PCI and 24 h after PCI. Univariate and multivariate logistic regression analyses were used to determine the relationship between preprocedural Lp(a) levels and postprocedural cTnI elevation from 1 × upper limit of normal (ULN) to 70 × ULN. As a continuous variable, multivariate analyses adjusting for conventional covariates and other serum lipids revealed that increased Lp(a) levels were independently associated with the risk of elevated postprocedural cTnI values above 1 × ULN (odds ratio [OR] per log-unit higher: 1.31, 95% confidence interval [CI]: 1.02-1.68, P = 0.033], 5 × ULN (OR: 1.25, 95%CI: 1.02-1.53, P = 0.032), 10 × ULN (OR: 1.48, 95%CI: 1.18-1.86, P = 0.001) and 15 × ULN (OR: 1.28, 95%CI: 1.01-1.61, P = 0.038). As a categorical variable, Lp(a) > 300 mg/L was an independent risk factor of postproceduralc TnI≥1 × ULN (OR 2.17, 95%CI 1.12-4.21, P = 0.022), ≥5 × ULN (OR 1.82, 95%CI 1.12-2.97, P = 0.017) and ≥10 × ULN (OR 2.17, 95%CI 1.33-3.54, P = 0.002). Therefore, it could be concluded that elevated preprocedural Lp(a) levels were associated with the risk of PCI-related myocardial injury in non-AMI CHD patients.

Lipid-based gene delivery to macrophage mitochondria for atherosclerosis therapy

Atherosclerosis with associated cardiovascular diseases remains one of the main causes of disability and death worldwide, requiring development of new solutions for prevention and treatment. Macrophages are the key effectors of a series of events involved in atherogenesis, such as inflammation, plaque formation, and changes in lipid metabolism. Some of these events were shown to be associated with mitochondrial dysfunction and excessive mitochondrial DNA (mtDNA) damage. Moreover, macrophages represent a promising target for novel therapeutic approaches that are based on the expression of various receptors and nanoparticle uptake. Lipid-based gene delivery to mitochondria is considered to be an interesting strategy for mtDNA damage correction. To date, several nanocarriers and their modifications have been developed that demonstrate high transfection efficiency and low cytotoxicity. This review discusses the possibilities of lipid-based gene delivery to macrophage mitochondria for atherosclerosis therapy.

Mathematical modeling for the prediction of cerebral white matter lesions based on clinical examination data

Cerebral white matter lesions are ischemic symptoms caused mainly by microangiopathy; they are diagnosed by MRI because they show up as abnormalities in MRI images. Because patients with white matter lesions do not have any symptoms, MRI often detects the lesions for the first time. Generally, head MRI for the diagnosis and grading of cerebral white matter lesions is performed as an option during medical checkups in Japan. In this study, we develop a mathematical model for the prediction of white matter lesions using data from routine medical evaluations that do not include a head MRI. Linear discriminant analysis, logistic discrimination, Naive Bayes classifier, support vector machine, and random forest were investigated and evaluated by ten-fold cross-validation, using clinical data for 1,904 examinees (988 males and 916 females) from medical checkups that did include the head MRI. The logistic regression model was selected based on a comparison of accuracy and interpretability. The model variables consisted of age, gender, plaque score (PS), LDL, systolic blood pressure (SBP), and administration of antihypertensive medication (odds ratios: 2.99, 1.57, 1.18, 1.06, 1.12, and 1.52, respectively) and showed Areas Under the ROC Curve (AUC) 0.805, the model displayed sensitivity of 72.0%, and specificity 75.1% when the most appropriate cutoff value was used, 0.579 as given by the Youden Index. This model has shown to be useful to identify patients with a high-risk of cerebral white matter lesions, who can then be diagnosed with a head MRI examination in order to prevent dementia, cerebral infarction, and stroke.