An 8-SNP LDL Cholesterol Polygenic Score: Associations with Cardiovascular Risk Traits, Familial Hypercholesterolemia Phenotype, and Premature Coronary Heart Disease in Central Romania.

Familial hypercholesterolemia (FH) is the most significant inherited risk factor for coronary heart disease (CHD). Current guidelines focus on monogenic FH, but the polygenic form is more common and less understood. This study aimed to assess the clinical utility of an 8-SNP LDLC polygenic score in a central Romanian cohort. The cohort included 97 healthy controls and 125 patients with premature (P)CHD. The weighted LDLC polygenic risk score (wPRS) was analyzed for associations with relevant phenotypic traits, PCHD risk, and clinical FH diagnosis. The wPRS positively correlated with LDLC and DLCN scores, and LDLC concentrations could be predicted by wPRS. A trend of increasing LDLC and DLCN scores with wPRS deciles was observed. A +1 SD increase in wPRS was associated with a 36% higher likelihood of having LDLC > 190 mg/dL and increases in LDLC (+0.20 SD), DLCN score (+0.16 SD), and BMI (+0.15 SD), as well as a decrease in HDLC (-0.14 SD). Although wPRS did not predict PCHD across the entire spectrum of values, individuals above the 90th percentile were three times more likely to have PCHD compared to those within the 10th or 20th percentiles. Additionally, wPRS > 45th percentile identified "definite" clinical FH (DLCN score > 8) with 100% sensitivity and 45% specificity. The LDLC polygenic score correlates with key phenotypic traits, and individuals with high scores are more likely to have PCHD. Implementing this genetic tool may enhance risk prediction and patient stratification. These findings, the first of their kind in Romania, are consistent with the existing literature.

Exploring the Role of Metabolic Hormones in Amyotrophic Lateral Sclerosis.

Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disease characterized by progressive loss of motor neurons. Emerging evidence suggests a potential link between metabolic dysregulation and ALS pathogenesis. This study aimed to investigate the relationship between metabolic hormones and disease progression in ALS patients. A cross-sectional study was conducted involving 44 ALS patients recruited from a tertiary care center. Serum levels of insulin, total amylin, C-peptide, active ghrelin, GIP (gastric inhibitory peptide), GLP-1 active (glucagon-like peptide-1), glucagon, PYY (peptide YY), PP (pancreatic polypeptide), leptin, interleukin-6, MCP-1 (monocyte chemoattractant protein-1), and TNFα (tumor necrosis factor alpha) were measured, and correlations with ALSFRS-R, evolution scores, and biomarkers were analyzed using Spearman correlation coefficients. Subgroup analyses based on ALS subtypes, progression pattern of disease, and disease progression rate patterns were performed. Significant correlations were observed between metabolic hormones and ALS evolution scores. Insulin and amylin exhibited strong correlations with disease progression and clinical functional outcomes, with insulin showing particularly robust associations. Other hormones such as C-peptide, leptin, and GLP-1 also showed correlations with ALS progression and functional status. Subgroup analyses revealed differences in hormone levels based on sex and disease evolution patterns, with male patients showing higher amylin and glucagon levels. ALS patients with slower disease progression exhibited elevated levels of amylin and insulin. Our findings suggest a potential role for metabolic hormones in modulating ALS progression and functional outcomes. Further research is needed to elucidate the underlying mechanisms and explore the therapeutic implications of targeting metabolic pathways in ALS management.

Low-Density Lipoprotein Cholesterol Gymnastics: Exploring the Advantages and Limitations of the Friedewald, Martin-Hopkins, and Sampson Equations for Personalized Lipid Management.

BACKGROUND: The most commonly used method for low-density lipoprotein cholesterol (LDL-C) estimation is the Friedewald equation, which has notable limitations. However, more accurate methods have been proposed. This study investigates the advantages and limitations of these methods and identifies the contexts in which each equation is the most or least applicable. METHODS: A cohort of 222 individuals underwent a standard lipid profile assessment, including directly measuring their LDL-C (dLDL-C). LDL-C was also estimated using the Friedewald, Martin-Hopkins, and Sampson equations. The differences (%Delta) between the estimated and measured LDL-C were analyzed in relation to dLDL-C, high-density lipoprotein cholesterol (HDL-C), and triglyceride levels. RESULTS: The %Delta was significantly lower (p < 0.0001) for the Martin-Hopkins (-8.8 ± 9.8) and Sampson (-9.5 ± 9.2) equations compared to Friedewald (-12.2 ± 9.2). All equations increasingly underestimated LDL-C as the dLDL-C levels decreased. The %Delta of the Martin-Hopkins equation showed significant positive correlations with dLDL-C (≤130 mg/dL) and triglycerides and a significant negative correlation with HDL-C. In a subgroup of 30 individuals with extreme %Delta values, patterns of gross underestimation were observed, particularly when low LDL-C, low triglycerides, and high HDL-C coincided. CONCLUSIONS: The Martin-Hopkins equation is a superior method for LDL-C estimation and a valuable tool in precision medicine. However, clinicians and laboratory professionals must be aware of its limitations and recognize patterns that could lead to significant LDL-C underestimation. We propose an algorithm for clinical laboratories to provide personalized LDL-C assessments.

A Review of Stage 0 Biomarkers in Type 1 Diabetes: The Holy Grail of Early Detection and Prevention?

Type 1 diabetes mellitus (T1D) is an incurable autoimmune disease characterized by the destruction of pancreatic islet cells, resulting in lifelong dependency on insulin treatment. There is an abundance of review articles addressing the prediction of T1D; however, most focus on the presymptomatic phases, specifically stages 1 and 2. These stages occur after seroconversion, where therapeutic interventions primarily aim to delay the onset of T1D rather than prevent it. This raises a critical question: what happens before stage 1 in individuals who will eventually develop T1D? Is there a "stage 0" of the disease, and if so, how can we detect it to increase our chances of truly preventing T1D? In pursuit of answers to these questions, this narrative review aimed to highlight recent research in the field of early detection and prediction of T1D, specifically focusing on biomarkers that can predict T1D before the onset of islet autoimmunity. Here, we have compiled influential research from the fields of epigenetics, omics, and microbiota. These studies have identified candidate biomarkers capable of predicting seroconversion from very early stages to several months prior, suggesting that the prophylactic window begins at birth. As the therapeutic landscape evolves from treatment to delay, and ideally from delay to prevention, it is crucial to both identify and validate such "stage 0" biomarkers predictive of islet autoimmunity. In the era of precision medicine, this knowledge will enable early intervention with the potential for delaying, modifying, or completely preventing autoimmunity and T1D in at-risk children.

A Review of the Prognostic Significance of Neutrophil-to-Lymphocyte Ratio in Nonhematologic Malignancies.

Biomarkers are crucial in cancer diagnostics, prognosis, and surveillance. Extensive research has been dedicated to identifying biomarkers that are broadly applicable across multiple cancer types and can be easily obtained from routine investigations such as blood cell counts. One such biomarker, the neutrophil-to-lymphocyte ratio (NLR), has been established as a prognostic marker in cancer. However, due to the dynamic nature of cancer diagnosis and treatment, periodic updates are necessary to keep abreast of the vast amount of published data. In this review, we searched the PubMed database and analyzed and synthesized recent literature (2018-February 2024) on the role of NLR in predicting clinical outcomes in nonhematologic malignancies. The search was conducted using the PubMed database. We included a total of 88 studies, encompassing 28,050 human subjects, and categorized the findings into four major groups: gastrointestinal cancer, cancers of the urinary tract and reproductive system, lung cancer, and breast cancer. Our analysis confirms that NLR is a reliable prognostic indicator in cancer, and we discuss the specific characteristics, limitations, and exceptions associated with its use. The review concludes with a concise Q&A section, presenting the most relevant take-home messages in response to five key practical questions on this topic.

Short-Term Atorvastatin Therapy in Healthy Individuals Results in Unaltered Plasma MMP Levels and Disrupted MMP-7 Correlation with Blood Lipids and Blood Count-Derived Inflammatory Markers.

Background: Matrix metalloproteinases (MMPs) play an important role in the pathophysiology of atherosclerosis. Reportedly, statins can decrease MMP activity in patients with atherosclerotic cardiovascular disease, but this effect has not been studied in healthy individuals. Methods: MMPs 2, 7, and 9 and several other parameters were measured before and after a four-week course of moderate-dose atorvastatin (20 mg/day) in 21 healthy individuals. Results: Atorvastatin treatment resulted in lower total cholesterol, LDL-cholesterol, non-HDL-cholesterol, and triglycerides (p < 0.001 for all), but higher levels of plasma enzymes AST, ALT, CK, and LDH (p < 0.05 for all). No effect of atorvastatin on plasma MMP median concentrations was recorded. Before treatment, moderate positive significant correlations were found between MMP-7 and age, blood lipids, and blood count-derived inflammatory markers. Pre-treatment MMP-7 was best predicted by the total cholesterol-to-HDL cholesterol ratio in a remnant cholesterol-weighted least squares regression model. After atorvastatin treatment, MMP-7 no longer correlated with these markers. Conclusions: While the effect of statins on plasma MMPs in atherosclerosis is controversial, short-term moderate-dose atorvastatin treatment does not seem to affect levels of MMPs 2, 7, and 9 in healthy individuals. However, an intriguing correlation between MMP-7 and atherosclerosis-related blood lipids and neutrophil-associated inflammatory biomarkers seems to be disrupted by atorvastatin independently of hsCRP, possibly via pleiotropic effects.

Long-Term Disability Outcomes in Relapsing-Remitting Multiple Sclerosis Patients: Impact of Clinical and Demographic Factors on Disease Progression.

Background: Multiple sclerosis (MS) is a prevalent chronic inflammatory and neurodegenerative disease of the central nervous system. The main evolving forms, relapsing-remitting MS (RRMS) and secondary progressive MS (SPMS), lack clear delineation. Methods: We conducted an observational study on 523 Caucasian RRMS patients receiving first-line disease-modifying therapies (DMTs), analyzing demographic, clinical, and geographical data. Results: RRMS patients experienced a statistically significant reduction in relapse rates post-DMT initiation. Significant differences in time to reach an Expanded Disability Status Score (EDSS) of 3.0 and 6.0 were observed based on demographics and onset topography. Kaplan-Meier analysis revealed that the onset with optic or supratentorial symptoms is linked to a longer time until EDSS = 3.0 is reached. Urban origin correlated with a prolonged time until EDSS = 3.0. Gender and environment showed no significant associations with the hazard of reaching an EDSS = 6.0. Cox regression analysis revealed no significant impact of relapses on the time to reach EDSS scores of 3.0 and 6.0 in our study cohort. Conclusions: Multivariate analysis identified several predictive factors for disability progression, including environment, age at onset, and disability level at DMT initiation.

Emerging Biomarkers for Predicting Clinical Outcomes in Patients with Heart Disease.

Cardiovascular disease is most frequently caused by the development and progression of atherosclerosis. When coronary arteries are afflicted, and the stenoses caused by atherosclerotic plaques are severe enough, the metabolic supply-and-offer balance is disturbed, leading to myocardial ischemia. If atherosclerotic plaques become unstable and local thrombosis develops, a myocardial infarction occurs. Sometimes, myocardial ischemia and infarction may result in significant and irreversible heart failure. To prevent severe complications, such as acute coronary syndromes and ischemia-related heart failure, extensive efforts have been made for developing biomarkers that would help identify patients at increased risk for cardiovascular events. In this two-part study, we attempted to provide a review of existing knowledge of blood biomarkers that may be used in this setting. The first part of this work was dedicated to conventional biomarkers, which are already used in clinical practice. In the second part, here presented, we discuss emerging biomarkers which have not yet become mainstream.

Conventional Biomarkers for Predicting Clinical Outcomes in Patients with Heart Disease.

Atherosclerosis is the main cause of cardiovascular disease worldwide. The progression of coronary atherosclerosis leads to coronary artery disease, with impaired blood flow to the myocardium and subsequent development of myocardial ischemia. Acute coronary syndromes and post-myocardial infarction heart failure are two of the most common complications of coronary artery disease and are associated with worse outcomes. In order to improve the management of patients with coronary artery disease and avoid major cardiovascular events, several risk assessment tools have been developed. Blood and imaging biomarkers, as well as clinical risk scores, are now available and validated for clinical practice, but research continues. The purpose of the current paper is to provide a review of recent findings regarding the use of humoral biomarkers for risk assessment in patients with heart disease.

Treatment With Cladribine Selects IFNγ+IL17+ T Cells in RRMS Patients - An In Vitro Study.

Background: Multiple sclerosis (MS) is an incurable autoimmune disease mediated by a heterogeneous T cell population (CD3+CD161+CXCR3-CCR6+IFNγ-IL17+, CD3+CXCR3+CCR6+IFNγ+IL17+, and CD3+CXCR3+IFNγ+IL17- phenotypes) that infiltrates the central nervous system, eliciting local inflammation, demyelination and neurodegeneration. Cladribine is a lymphocyte-depleting deoxyadenosine analogue recently introduced for MS therapy as a Disease Modifying Drug (DMD). Our aim was to establish a method for the early identification and prediction of cladribine responsiveness among MS patients. Methods: An experimental model was designed to study the cytotoxic and immunomodulatory effect of cladribine. T cell subsets of naïve relapsing-remitting MS (RRMS) patients were analyzed ex vivo and in vitro comparatively to healthy controls (HC). Surviving cells were stimulated with rh-interleukin-2 for up to 14days. Cell proliferation and immunophenotype changes were analyzed after maximal (phorbol myristate acetate/ionomycin/monensin) and physiological T-cell receptor (CD3/CD28) activation, using multiparametric flow cytometry and xMAP technology. Results: Ex vivo CD161+Th17 cells were increased in RRMS patients. Ex vivo to in vitro phenotype shifts included: decreased CD3+CCR6+ and CD3+CD161+ in all subjects and increased CD3+CXCR3+ in RRMS patients only; Th17.1 showed increased proliferation vs Th17 in all subjects; CD3+IL17+ and CD3+IFNγ+IL17+ continued to proliferate till day 14, CD3+IFNγ+ only till day 7. Regarding cladribine exposure: RRMS CD3+ cells were more resistant compared to HC; treated CD3+ cells proliferated continuously for up to 14 days, while untreated cells only up to 7 days; both HC/RRMS CD3+CXCR3+ populations increased from baseline till day 14; in RRMS patients vs HC, IL17 secretion from cladribine-treated cells increased significantly, in line with the observed proliferation of CD3+IL17+ and CD3+IFNγ+IL17+ cells; in both HC/RRMS, cladribine led to a significant increase in CD3+IFNγ+ cells at day 7 only, having no further effect at day14. IFNγ and IL17 secreted in culture media decreased significantly from ex vivo to in vitro. Conclusions: CD3+ subtypes showed different responsiveness due to selectivity of cladribine action, in most patients leading to in vitro survival/proliferation of lymphocyte subsets known as pathogenic in MS. This in vitro experimental model is a promising tool for the prediction of individual responsiveness of MS patients to cladribine and other DMDs.