Search Results (1,710)

Background/Objectives: Hyperlipidemia is a major risk factor for cardiovascular disease and atherosclerosis. Polyphenols found in polyphenol-rich extra virgin olive oil (EVOO) have been shown to possess strong antioxidant, anti-inflammatory, and cardioprotective properties. The present study aimed to assess the effects of two types of EVOO with different polyphenol content and dosages on the lipid profile of hyperlipidemic patients. Methods: In this single-blind, randomized clinical trial, 50 hyperlipidemic patients were randomized to receive either a higher-dose, lower-phenolic EVOO (414 mg/kg phenols, 20 g/day) or a lower-dose, higher-phenolic EVOO (1021 mg/kg phenols, 8 g/day), for a period of 4 weeks. These doses were selected to ensure equivalent daily polyphenol intake in both groups (~8.3 mg of total phenols/day), based on chemical analysis performed using NMR spectroscopy. The volumes used (8–20 g/day) reflect typical daily EVOO intake and were well tolerated by participants. A group of 20 healthy individuals, separated into two groups, also received the two types of EVOO, respectively, for the same duration. Primary endpoints included blood levels of total blood cholesterol, low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglycerides, lipoprotein-a (Lpa), and apolipoproteins A1 and B. Measurements were performed at baseline and at the end of the 4-week intervention. Linear mixed models were performed for the data analysis. Results: The higher-phenolic, lower-dose EVOO group showed a more favorable change in total blood cholesterol (p = 0.045) compared to the lower-phenolic, higher-dose group. EVOO intake was associated with a significant increase in HDL (p < 0.001) and reduction in Lp(a) (p = 0.040) among hyperlipidemic patients in comparison to healthy individuals. Conclusions: EVOO consumption significantly improved the lipid profile of hyperlipidemic patients. Higher-phenolic EVOO at lower dosages appears to be more effective in improving the lipid profile than lower-phenolic EVOO in higher dosages. Full article

Acute hepatopancreatic necrosis disease (AHPND), caused by the bacterium Vibrio parahaemolyticus, is a major threat to global shrimp aquaculture. In this study, we evaluated the therapeutic effects of phage therapy in Litopenaeus vannamei challenged with AHPND-causing Vibrio parahaemolyticus. Phage application at various concentrations significantly improved shrimp survival, with the 1 ppm group demonstrating the highest survival rate. Enzymatic assays revealed that phage-treated shrimp exhibited enhanced immune enzyme activities, including acid phosphatase (ACP), alkaline phosphatase (AKP), and lysozyme (LZM). In addition, antioxidant defenses such as superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GSH-PX), and total antioxidant capacity (T-AOC) significantly improved, accompanied by reduced malondialdehyde (MDA) levels. Serum biochemical analyses demonstrated marked improvements in lipid metabolism, particularly reductions in triglyceride (TG), total cholesterol (TC), and low-density lipoprotein (LDL), alongside higher levels of beneficial high-density lipoprotein (HDL). Transcriptomic analysis identified 2274 differentially expressed genes (DEGs), notably enriched in pathways involving fatty acid metabolism, peroxisome functions, lysosomes, and Toll-like receptor (TLR) signaling. Specifically, phage treatment upregulated immune and metabolic regulatory genes, including Toll-like receptor 4 (TLR4), myeloid differentiation primary response protein 88 (MYD88), interleukin-1β (IL-1β), nuclear factor erythroid 2-related factor 2 (Nrf2), and peroxisome proliferator-activated receptor (PPAR), indicating activation of innate immunity and antioxidant defense pathways. These findings suggest that phage therapy induces protective immunometabolic adaptations beyond its direct antibacterial effects, thereby providing an ecologically sustainable alternative to antibiotics for managing bacterial diseases in shrimp aquaculture. Full article

Metabolic and bariatric surgery (MBS) is an effective treatment for severe obesity, though individual responses vary widely, partly due to genetic predisposition. This study investigates the association of a body mass index (BMI) polygenic score (PGS) with weight loss and metabolic outcomes following surgery. A cohort of 225 patients undergoing MBS was analyzed at baseline (T₀), six (T₆), and twelve (T₁₂) months, with anthropometric and biochemical parameters recorded at each time point. Total weight loss (TWL) and excess weight loss (EWL) percentages were calculated. PGS was computed using the LDpred-grid Bayesian method. The mean age was 45.9 ± 9.4 years. Males had a higher baseline prevalence of type 2 diabetes (T2D) and comorbidities (p < 0.001). Linear regression analysis confirmed an association between PGS and baseline BMI (p = 0.012). Moreover, mediation analysis revealed that baseline BMI mediated the effect of the PGS on %TWL at T₁₂, with an indirect effect (p-value = 0.018). In contrast, high-density lipoprotein-cholesterol (HDL-C) at T₆ and triglycerides (TG) at T₁₂ showed direct associations with the PGS (p-value = 0.004 and p-value = 0.08, respectively), with no significant mediation by BMI. This study showed a BMI-mediated association of PGS with %TWL and a direct association with lipid changes, suggesting its potential integration into personalized obesity treatment. Full article

Background: Type 2 diabetes (T2D) and overweight or obesity are strongly associated, with a high prevalence of these concomitant conditions contributing significantly to global healthcare costs. Given this burden, there is an urgent need for effective interventions. Mobile health (mHealth) technologies represent a promising strategy to address both conditions simultaneously. Objectives: This systematic review and meta-analysis aimed to evaluate the effectiveness of mHealth-based interventions for the management of adults with T2D and overweight/obesity. Specifically, it assessed the quantitative impact of these interventions on glycosylated hemoglobin (HbA1c), body weight, triglycerides, total cholesterol, low-density lipoprotein (LDL), and high-density lipoprotein (HDL) levels. Methods: A systematic search was conducted in PubMed, Web of Science, and Scopus databases from inception to 9 July 2025. The inclusion criteria focused on randomized controlled trials (RCTs) using mHealth interventions in adults with T2D and overweight/obesity, reporting HbA1c or weight as primary or secondary outcomes. The risk of bias was assessed using the Cochrane Risk of Bias tool 2. A total of 13 RCTs met the inclusion criteria. Results: Meta-analysis indicated significant improvements after 6–12 months of intervention in HbA1c (MD −0.23; 95% CI −0.36 to −0.10; p < 0.001; I² = 72%), body weight (MD −2.47 kg; 95% CI −3.69 to −1.24; p < 0.001; I² = 79%), total cholesterol (MD −0.23; 95% CI −0.39 to −0.07; p = 0.004; I² = 0%), and LDL (MD −0.27; 95% CI −0.42 to −0.12; p < 0.001; I² = 0%). Conclusions: mHealth interventions are effective and scalable for managing T2D and obesity, particularly when incorporating wearable technologies to improve adherence. Future research should focus on optimizing personalization, engagement strategies, and long-term implementation. Full article

Background: The global increase in type 2 diabetes mellitus (T2DM) cases necessitates the need for early detection of metabolic changes. This study investigated variations in liver enzymes, renal markers, electrolytes, and lipid profiles among T2DM patients stratified by hemoglobin A1c (HbA1c) categories to support early identification and better management of diabetes-related complications. Methods: A retrospective observational study at King Khalid University Hospital (KKUH), Riyadh, included 621 adult patients diagnosed with T2DM categorized into four HbA1c groups: normal (<5.7%), prediabetes (5.7–6.4%), controlled diabetes (6.5–7.9%), and uncontrolled diabetes (≥8.0%). Biochemical parameters included the liver profile: alkaline phosphatase (ALP) and bilirubin, renal profile: creatinine, blood urea nitrogen (BUN), glucose, sodium, and chloride, and lipid profile: cholesterol, high-density lipoprotein (HDL), low-density lipoprotein (LDL), and triglycerides. Regression models identified predictors of ALP, cholesterol, and LDL. Results: ALP was higher in uncontrolled diabetes (89.0 U/L, Q1–Q3: 106.3–72.0) than in the prediabetes group (75.0 U/L, Q1–Q3: 96.8–62.3). Sodium and chloride were lower in uncontrolled diabetes (Na: 138.3 mmol/L, Q1–Q3: 140.3–136.4; Cl: 101.1 mmol/L, Q1–Q3: 102.9–99.4) compared to the normal group (Na: 139.5 mmol/L, Q1–Q3: 142.4–136.9; Cl: 103.5 mmol/L, Q1–Q3: 106.1–101.7). LDL was lower in uncontrolled diabetes (2.1 mmol/L, Q1–Q3: 2.8–1.7) than in the normal group (2.8 mmol/L, Q1–Q3: 3.7–2.2), while triglycerides were higher in patients with uncontrolled diabetes compared to the normal group (1.45 mmol/L, Q1–Q3: 2.02–1.11 vs. 1.26 mmol/L, Q1–Q3: 1.44–0.94). Regression models showed low explanatory power (R² = 2.1–7.3%), with weight, age, and sex as significant predictors of select biochemical markers. Conclusions: The study observed biochemical variations across HbA1c categories in T2DM patients, likely reflecting insulin resistance. Monitoring these markers in conjunction with HbA1c can enhance early detection and improve the management of complications. Full article

Background: Metabolic syndrome (MetS) is a multifactorial condition involving central obesity, dyslipidemia, hypertension, and impaired glucose metabolism, significantly increasing the risk of type 2 diabetes and cardiovascular disease. Objectives: Given the clinical heterogeneity of MetS, this study aimed to identify distinct metabolic phenotypes, referred to as metabotypes, using validated biomarkers and to examine their association with MetS. Materials and Methods: A total of 1245 Korean adults aged 19–79 years were selected from the 2016–2023 Korea National Health and Nutrition Examination Survey. Metabotype risk clusters were derived using k-means clustering based on five biomarkers: body mass index (BMI), uric acid, fasting blood glucose (FBG), high-density lipoprotein cholesterol (HDLc), and non-HDL cholesterol (non-HDLc). Multivariable logistic regression was used to assess associations with MetS. Results: Three distinct metabotype risk clusters (low, intermediate, and high risk) were identified. The high-risk cluster exhibited significantly worse metabolic profiles, including elevated BMI, FBG, HbA1c, triglyceride, and reduced HDLc. The prevalence of MetS increased progressively across metabotype risk clusters (OR: 5.46, 95% CI: 2.89–10.30, p < 0.001). In sex-stratified analyses, the high-risk cluster was strongly associated with MetS in both men (OR: 9.22, 95% CI: 3.49–24.36, p < 0.001) and women (OR: 3.70, 95% CI: 1.56–8.75, p = 0.003), with notable sex-specific differences in lipid profiles, particularly in HDLc. Conclusion: These findings support the utility of metabotyping using routine biomarkers as a tool for early identification of high-risk individuals and the development of personalized prevention strategies in clinical and public health settings. Full article

Background and Objectives: Despite significant advances in surgical techniques and perioperative care, major adverse cardiovascular events (MACE) remain a leading cause of postoperative morbidity and mortality in patients undergoing coronary artery bypass grafting and/or aortic valve replacement. Accurate preoperative risk stratification is essential yet often limited by models that overlook atrial mechanics and underutilized biomarkers. Materials and Methods: This study aimed to develop an interpretable machine learning model for predicting perioperative MACE by integrating clinical, biochemical, and echocardiographic features, with a particular focus on novel physiological markers. A retrospective cohort of 131 patients was analyzed. An Extreme Gradient Boosting (XGBoost) classifier was trained on a comprehensive feature set, and SHapley Additive exPlanations (SHAPs) were used to quantify each variable’s contribution to model predictions. Results: In a stratified 80:20 train–test split, the model initially achieved an AUC of 1.00. Acknowledging the potential for overfitting in small datasets, additional validation was performed using 10 independent random splits and 5-fold cross-validation. These analyses yielded an average AUC of 0.846 ± 0.092 and an F1-score of 0.807 ± 0.096, supporting the model’s stability and generalizability. The most influential predictors included total atrial conduction time, mitral and tricuspid annular orifice areas, and high-density lipoprotein (HDL) cholesterol. These variables, spanning electrophysiological, structural, and metabolic domains, significantly enhanced discriminative performance, even in patients with preserved left ventricular function. The model’s transparency provides clinically intuitive insights into individual risk profiles, emphasizing the significance of non-traditional parameters in perioperative assessments. Conclusions: This study demonstrates the feasibility and potential clinical value of combining advanced echocardiographic, biochemical, and machine learning tools for individualized cardiovascular risk prediction. While promising, these findings require prospective validation in larger, multicenter cohorts before being integrated into routine clinical decision-making. Full article

Obesity is currently one of the most critical public health problems. Although there is no doubt that obesity is a significant risk factor for developing metabolic disorders, this relationship is not completely straightforward. On the one hand, some patients affected by obesity are metabolically unhealthy, while others are metabolically healthy; on the other hand, metabolic syndrome (MetS) can also occur in people with a normal body weight. A commonly used tool for diagnosing obesity is the body mass index (BMI), but the search for better anthropometric measures is ongoing due to the significant limitations of this measure. Obesity can lead to MetS and cardiovascular diseases (CVDs). Adipose tissue dysfunction is the fundamental mechanism linking obesity and cardiometabolic diseases, which is rooted in the disturbed secretion of adipokines. The visceral adiposity index (VAI) is calculated based on the BMI, waist circumference (WC), blood triglycerides (TG), and high-density lipoprotein cholesterol (HDL-C) concentrations. It was proposed in 2010 by Amato et al. as a parameter indicating adipose tissue dysfunction and cardiometabolic risk. According to the research conducted so far, some data confirm a relationship between the VAI value and the risk of developing prediabetes, diabetes, insulin resistance, fatty liver disease, MetS, CVD, and chronic kidney disease. Further research is needed to support the implementation of VAI assessment in routine clinical practice. The purpose of this paper is to present the results of a narrative literature review summarizing current knowledge regarding the VAI and its usefulness in clinical practice for assessing cardiometabolic risk. Full article

Background/Objectives: Carnitine deficiency is common in hemodialysis patients and may contribute to anemia, inflammation, dyslipidemia, and muscle symptoms. This review explores the potential benefits of L-carnitine supplementation in this population. Methods: A thorough literature search of the PubMed database was conducted to identify clinical trials and studies assessing the effects of L-carnitine supplementation on adult hemodialysis patients. Key outcomes included the effects on inflammation, lipid profile, anemia, glycemic control, and muscle function. Results: Evidence suggests that L-carnitine may reduce inflammatory markers and improve lipid profiles by lowering triglycerides and increasing high-density lipoprotein (HDL). Several studies reported reduced erythropoietin need and improved hemoglobin levels. However, some studies did not find benefits of carnitine supplementation on the mentioned parameters. Results for muscle cramps, glycemic control, and cardiac function remain inconsistent. Conclusions: L-carnitine supplementation shows potential benefits in the management of hemodialysis complications. However, further well-designed trials are needed to confirm efficacy and optimize treatment protocols. Full article

Cardiovascular disease (CVD), particularly atherosclerotic cardiovascular disease (ASCVD), is the leading cause of death worldwide, driven by factors like oxidative stress, inflammation, and lipid metabolism disorders. Although phenolic compounds such as Tyrosol (Tyr) and Hydroxytyrosol (HTyr) found in extra virgin olive oil (EVOO) have shown promising antioxidant and anti-inflammatory effects, their specific roles in modulating oxidative stress biomarkers and high-density lipoprotein (HDL) functionality in elderly populations, especially in those with prior myocardial infarction, are not fully understood. This study aimed to investigate the effects of EVOO phenolic compounds on oxidative stress biomarkers and HDL functionality, and related metabolic outcomes in both healthy and post-myocardial infarction (post-MI) elderly individuals. This pilot randomized clinical trial study included healthy and post-MI participants aged 65–85 years. Participants in each group were randomly assigned to consume 25 mL per day of one of three types of olive oils: high phenolic (HTyr/Tyr) extra virgin olive oil (HP-EVOO), extra virgin olive oil (EVOO), or refined olive oil (ROO) for a period of 26 weeks. Blood samples were collected at baseline and post-intervention to assess key biomarkers. Plasma levels of (poly)phenols, malondialdehyde (MDA), total antioxidant capacity (FRAP), lecithin-cholesterol acyltransferase activity (LCAT), and serum paraoxonase-1 (PON-1) activity were measured. A total of 34 individuals completed the study (mean age: 74 years). Baseline characteristics, including sex, age, body mass index (BMI), weight, blood pressure, and inflammatory markers like C-reactive protein (CRP) levels, did not differ significantly between the two groups. A significant increase in both FRAP levels and PON-1 activity was observed in post-MI participants following HP-EVOO consumption compared to baseline (p = 0.014). No significant changes were observed in MDA levels, LCAT activity, or plasma (poly)phenols. These results indicate that HP-EVOO may enhance antioxidant capacity, particularly FRAP and PON-1 activity, in elderly post-MI individuals. The observed differences between groups suggest that underlying cardiometabolic status may influence the response to olive oil phenolic compounds. Further studies are needed to explore the long-term cardiovascular effects. Full article

Background: High-density lipoprotein cholesterol (HDL-C) is known for its cardiovascular and neuroprotective effects, but its association with cognitive function remains unclear, particularly in relation to genetic factors such as apolipoprotein E ε4 (APOE4). We aimed to investigate the association between serum HDL-C levels and cognition and to examine the moderating effect of APOE4 on this relationship. Methods: This cross-sectional study included 196 dementia-free older adults (aged 65–90) recruited from a memory clinic and the community. Cognitive function was assessed across multiple domains using the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) battery. Serum HDL-C levels were measured, and APOE4 genotyping was performed. Multiple linear regression analyses were conducted, adjusting for age, sex, APOE4 status, education, diagnosis, vascular risk, nutritional status, physical activity, and blood biomarkers. Results: Higher HDL-C levels were significantly associated with better episodic memory (B = 0.109, 95% confidence interval [CI]: 0.029–0.189, p = 0.008) and global cognition (B = 0.130, 95% CI: 0.001–0.261, p = 0.049). These associations were significantly moderated by APOE4 status. In APOE4-positive individuals, HDL-C was strongly associated with both episodic memory (B = 0.357, 95% CI: 0.138–0.575, p = 0.003) and global cognition (B = 0.519, 95% CI: 0.220–0.818, p = 0.002), but no such associations were observed in APOE4-negative participants. Conclusions: This study indicates a significant association between serum HDL-C levels and cognitive function, particularly in episodic memory and global cognition, with APOE4 status potentially moderating this relationship. While these findings may suggest a protective role of HDL-C in individuals at increased genetic risk due to APOE4, they should be interpreted with caution given the cross-sectional design. Future longitudinal and mechanistic studies are warranted to clarify causality and potential clinical implications. Full article

Background: Childhood obesity is a significant global health concern. Butyrylcholinesterase (BChE) has been shown to play a role in lipid metabolism. This study aimed to assess BChE activity, obesity-related and lipid-related indices, and dyslipidemia in obese and non-obese children, and to investigate the associations of these parameters with obesity among Thai children. Methods: The study included 661 Thai children, consisting of 338 with obesity and 323 with a normal weight. Anthropometric measurements, metabolic parameters, obesity- and lipid-related indices, and BChE activity were evaluated. Results: The obese group exhibited significantly higher BChE activity and obesity-related and lipid-related indices compared to the non-obese group (p < 0.01). Additionally, metabolic parameters—including glucose levels, triglyceride-glucose (TyG) index, and TyG-related indices—as well as the lipid profile, which included triglycerides (TG), non-high-density lipoprotein cholesterol (non-HDL-C), and very-low-density lipoprotein cholesterol (VLDL-C), were all significantly elevated in the obese group (p < 0.01). Obesity was associated with dyslipidemia (p < 0.01). Moreover, BChE activity showed a positive correlation with obesity-related and lipid-related indices, along with several metabolic parameters (p < 0.002). The upper stratum of BChE activity (OR = 5.356), the non-HDL-C/HDL-C ratio (OR = 2.185), and the TG/HDL-C ratio (OR = 1.703) were found to be effective in evaluating and predicting the risk of obesity, even after adjusting for potential covariates (p < 0.01). Conclusions: These findings indicate a significant relationship between obesity and increased BChE activity, lipid-related indices, and dyslipidemia in Thai children. Therefore, changes in BChE activity may be considered a factor associated with obesity, enhancing its potential as a marker for obesity assessment. Full article

High-density lipoprotein (HDL) and small dense low-density lipoprotein (sdLDL) represent two critical yet contrasting components in lipid metabolism and cardiovascular risk modulation. While HDL has traditionally been viewed as cardioprotective due to its role in reverse cholesterol transport and anti-inflammatory effects, emerging evidence emphasizes that HDL functionality—rather than concentration alone—is pivotal in atheroprotection. Conversely, sdLDL particles are increasingly recognized as highly atherogenic due to their enhanced arterial penetration, oxidative susceptibility, and prolonged plasma residence time. This review critically examined the physiological roles, pathological implications, and therapeutic interventions targeting HDL function and sdLDL burden. Lifestyle modifications, pharmacologic agents including statins, fibrates, PCSK9 inhibitors, and novel therapies such as icosapent ethyl were discussed in the context of their effects on HDL quality and sdLDL reduction. Additionally, current clinical guidelines were analyzed, highlighting a paradigm shift away from targeting HDL-C levels toward apoB-driven risk reduction. Although HDL-targeted therapies remain under investigation, the consensus supports focusing on lowering apoB-containing lipoproteins while leveraging lifestyle strategies to improve HDL functionality. In the setting of heart failure, particularly with preserved ejection fraction (HFpEF), alterations in HDL composition and elevated sdLDL levels have been linked to endothelial dysfunction and systemic inflammation, further underscoring their relevance beyond atherosclerosis. A comprehensive understanding of HDL and sdLDL dynamics is essential for optimizing cardiovascular prevention strategies. Full article

Background/Objectives: Anorexia nervosa (AN) is a chronic eating disorder with the highest mortality rate among psychiatric conditions. Malnutrition and starvation lead to long-term impairments in metabolic processes, hormonal regulation, and immune function, offering potential diagnostic and prognostic value. This study aimed to identify immune–metabolic–hormonal markers associated with treatment response and nutritional rehabilitation. Methods: Fifty hospitalized female patients with AN were included. Anthropometric measurements and venous blood samples were collected at admission and discharge, following partial nutritional recovery. Blood analyses included complete blood count, serum levels of total cholesterol, LDL and HDL, triglycerides, glucose, NT-pro-BNP, TSH, free thyroxine (fT4), sodium, chloride, potassium, calcium, iron, and vitamin D. Composite immune-inflammatory indices calculated were neutrophil-to-lymphocyte (NLR), monocyte-to-lymphocyte (MLR), platelet-to-lymphocyte (PLR); neutrophil-to-high-density lipoprotein (NHR), monocyte-to-high-density lipoprotein (MHR), platelet-to-high-density lipoprotein (PHR) and lymphocyte-to-high-density lipoprotein (LHR) ratios; systemic immune-inflammation (SII), and systemic inflammation response (SIRI) indexes. Results: Responders (R) and non-responders (NR) differed significantly at baseline in levels of sodium, chloride, fT4, monocyte count, MCV, NLR, MLR, SII, and SIRI (all: R < NR; p < 0.05). Predictive ability for treatment response was confirmed by AUC values (95%CI): sodium = 0.791 (0.622–0.960), chloride = 0.820 (0.690–0.950), fT4 = 0.781 (0.591–0.972), monocytes = 0.785 (0.643–0.927), MCV = 0.721 (0.549–0.892), NLR = 0.745 (0.578–0.913), MLR = 0.785 (0.643–0.927), SII = 0.736 (0.562–0.911), SIRI = 0.803 (0.671–0.935). The lower levels of inflammation and chloride are particularly predictive of better nutritional recovery, accounting for 26% of the variability in treatment response. Conclusions: The study demonstrated important insights into the hematological, metabolic, hormonal, and immune-inflammatory mechanisms associated with nutritional recovery in AN. Full article

Recent findings have identified high-density lipoprotein (HDL) as a carrier of microRNAs, small non-coding RNAs that regulate gene expression, suggesting a potential novel functional and biochemical role for HDL-microRNA cargo. Here, we conduct an in-depth bioinformatics analysis of unique HDL-microRNA cargo to uncover their molecular mechanisms and potential applications as clinical biomarkers. First, using the Gene Expression Omnibus (GEO), we performed computational analysis on public human microRNA array datasets (GSE 25425; platform GPL11162) obtained from highly purified fractions of HDL in human plasma in order to identify their unique miRNA cargo. This led to the identification of eleven miRNAs present only in HDL, herein listed: hsa-miR-210, hsa-miR-26a-1, hsa-miR-628-3p, hsa-miR-31, hsa-miR-501-5p, hsa-miR-100-3p, hsa-miR-571, hsa-miR-100-5p, hsa-miR-23a, hsa-miR-550, and hsa-miR-432. Then, these unique miRNAs present in HDL were analyzed using a bioinformatics approach to recognize their validated target genes. The ClusterProfiler R package applied gene ontology and KEGG enrichment analysis. The key genes mainly enriched in the biological process of cellular regulation were identified and linked to neurodegeneration. Finally, the protein–protein interaction and co-expression network were analyzed using the STRING and GeneMANIA Cytoscape plugins. Full article