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Background: Genetic risk scores (GRSs) have partially improved the understanding of the etiology of moderate hypertriglyceridemia (HTG), which until recently was mainly assessed by secondary predisposing causes. The main objective of this study was to assess whether this variability is due to the interaction between clinical variables and GRS. Methods: We analyzed 276 patients with suspected polygenic HTG. An unweighted GRS was developed with the following variants: c.724C > G (ZPR1 gene), c.56C > G (APOA5 gene), c.1337T > C (GCKR gene), g.19986711A > G (LPL gene), c.107 + 1647T > C (BAZ1B gene) and g.125478730A > T (TRIB gene). Interactions between the GRS and clinical variables (body mass index (BMI), diabetes mellitus, diet, physical activity, alcohol consumption, age and gender) were evaluated. Results: The GRS was associated with triglyceride (TG) concentrations. There was a significant interaction between BMI and GRS, with the intensity of the relationship between the number of alleles and the TG concentration being greater in individuals with a higher BMI. Conclusions: GRS is associated with plasma TG concentrations and is markedly influenced by BMI. This finding could improve the stratification of patients with a high genetic risk for HTG who could benefit from more intensive healthcare interventions.

Background: Hereditary hemorrhagic telangiectasia (HHT) is a rare vascular disease inherited in an autosomal dominant manner. Disease-causing variants in endoglin (ENG) and activin A receptor type II-like 1 (ACVRL1) genes are detected in more than 90% of the patients undergoing molecular testing. The identification of variants of unknown significance is often seen as a challenge in clinical practice that makes family screening and genetic counseling difficult. Here, we show that the implementation of cDNA analysis to assess the effect of splice site variants on mRNA splicing is a powerful tool. Methods: Gene panel sequencing of genes associated with HHT and other arteriovenous malformation-related syndromes was performed. To evaluate the effect of the splice site variants, cDNA analysis of ENG and ACVRL1 genes was carried out. Results: three novel splice site variants were identified in ENG (c.68-2A > T and c.1311+4_1311+8del) and ACVLR1 (c.526-6C > G) genes correspondingly in three individuals with HHT that met ≥ 3 Curaçao criteria. All three variants led to an aberrant splicing inducing exon skipping (ENG:c.68-2A > T and ACVRL1:c.526-6C > G) or intron retention (ENG:c.1311+4_1311+8del) allowing the confirmation of the predicted effect on splicing and the reclassification from unknown significance to pathogenic/likely pathogenic of two of them. Conclusions: RNA analysis should be performed to assess and/or confirm the impact of variants on splicing. The molecular diagnosis of HHT patients is crucial to allow family screening and accurate genetic counseling. A multidisciplinary approach including clinicians and geneticists is crucial when dealing with patients with rare diseases.

SLE is associated with increased cardiovascular risk. The objective of this study was to determine the prevalence of asymptomatic carotid atherosclerosis to analyze its relationship with dyslipidemia and related genetic factors in a population of patients with SLE. Seventy-one SLE female patients were recruited. Carotid ultrasound, laboratory profiles, and genetic analysis of the ZPR1, APOA5, and GCKR genes were performed. SLE patients were divided into two groups according to the presence or absence of carotid plaques. Patients with carotid plaque had higher plasma TG (1.5 vs. 0.9 mmol/L, p = 0.001), Non-HDL-C (3.5 vs. 3.1 mmol/L, p = 0.025), and apoB concentrations (1.0 vs. 0.9 g/L, p = 0.010) and a higher prevalence of hypertension (80 vs. 37.5%, p = 0.003) than patients without carotid plaque. The GCKR C-allele was present in 83.3% and 16.7% (p = 0.047) of patients with and without carotid plaque, respectively. The GCKR CC genotype (OR = 0.026, 95% CI: 0.001 to 0.473, p = 0.014), an increase of 1 mmol/L in TG concentrations (OR = 12.550, 95% CI: 1.703 to 92.475, p = 0.013) and to be hypertensive (OR = 9.691, 95% CI: 1.703 to 84.874, p = 0.040) were independently associated with carotid atherosclerosis. In summary, plasma TG concentrations, CGKR CC homozygosity, and hypertension are independent predictors of carotid atherosclerosis in women with SLE.

Altres ajuts: Fondo Europeo de Desarrollo Regional (FEDER). Some lipoprotein disorders related to the residual risk of premature cardiovascular disease (PCVD) are not detected by the conventional lipid profile. In this case-control study, the predictive power of PCVD of serum sdLDL-C, measured using a lipoprotein precipitation method, and of the physicochemical properties of serum lipoproteins, analyzed by nuclear magnetic resonance (NMR) techniques, were evaluated. We studied a group of patients with a first PCVD event (n = 125) and a group of control subjects (n = 190). Conventional lipid profile, the size and number of Very Low Density Lipoproteins (VLDL), Low Density Lipoproteins (LDL), High Density Lipopro-teins (HDL) particles, and the number of particles of their subclasses (large, medium, and small) were measured. Compared to controls, PCVD patients had lower concentrations of all LDL parti-cles, and smaller and larger diameter of LDL and HDL particles, respectively. PCVD patients also showed higher concentrations of small dense LDL-cholesterol (sdLDL), and triglycerides (Tg) in LDL and HDL particles (HDL-Tg), and higher concentrations of large VLDL particles. Multivariate logistic regression showed that sdLDL-C, HDL-Tg, and large concentrations of LDL particles were the most powerful predictors of PCVD. A strong relationship was observed between increased HDL-Tg concentrations and PCVD. This study demonstrates that beyond the conventional lipid profile, PCVD patients have other atherogenic lipoprotein alterations that are detected by magnetic resonance imaging (MRI) analysis.

Diagnosis and treatment of triglyceride metabolism disorders: from pathophysiology to clinical practice. Hypertriglyceridaemia (HTG) affects 15%-20% of the world's population, and is frequently discovered as an incidental finding in a laboratory test. Disorders of triglyceride (TG) metabolism have a complex genetic basis. New genetic tools that allow a more precise approach to the disorders have made it possible to redefine and classify HTG into two groups: monogenic HTG (TG10 mmol/L) and polygenic HTG (2 mmol/LTG10 mmol/L) with a milder phenotype, but with a clear genetic influence. In approximately 50% of patients with severe HTG a genetic cause has not yet been found. In addition to the inclusion of ever more genes in studies, statistical models are now also being examined that consider complex gene-environment interactions that could explain why the presence of a set of apparently benign variants may cause HTG in the presence of a triggering factor such as adiposity. Knowledge of the genetic nature of HTG has also helped identify targets for pharmacological treatments, thus avoiding a strict diet with a fat content of less than 20%, which is difficult to maintain. Accurate diagnosis of these disorders is essential for correct treatment according to the inherent risk of each HTG, since, as has been shown in multiple studies, high fasting and postprandial TG concentrations are an independent risk factor for cardiovascular disease.

Background: Lipid metabolism disorders, especially hypertriglyceridemia (HTG), are risk factors for non-alcoholic fatty liver disease (NAFLD). However, the association between genetic factors related to HTG and the risk of NAFLD has been scarcely studied. Methods: A total of 185 subjects with moderate HTG were prospectively included. We investigated the association between genetic factors’ (five allelic variants with polygenic hypertriglyceridemia) clinical and biochemical biomarkers with NAFLD severity. The five allelic variants’ related clinical and biochemical data of HTG were studied in all the subjects. NAFLD was assessed by abdominal ultrasound and patients were divided into two groups, one with no or mild NAFLD and another with moderate/severe NAFLD. Results: Patients with moderate/severe NAFLD had higher weight and waist values and a higher prevalence of insulin resistance than patients with no or mild NAFLD. Moderate/severe NAFLD was independently associated with APOA5 rs3134406 and ZPR1 rs964184 variants, and also showed a significant inverse relationship with lipoprotein(a) [Lp(a)] concentrations. Conclusions: APOA5 rs3135506 and ZPR1 rs964184 variants and lipoprotein(a) are associated with moderate/severe NAFLD. This association was independent of body weight, insulin resistance, and other factors related to NAFLD. info:eu-repo/semantics/publishedVersion

International audience; Background LDL-C lowering is the main measure in cardiovascular disease prevention but a residual risk of ischemic events still remains. Alterations of lipoproteins, specially, increase in small dense LDL (sdLDL) particles are related to this risk.Objective To investigate the potential use of sdLDL cholesterol concentration (sdLDL-C) isolated by an easy precipitation method and to assess the impact of a set of clinical and biochemical variables determined by NMR on sdLDL concentration.Methods sdLDL-C and NMR lipid profile were performed in 85 men samples. Association among them was evaluated using Pearson coefficients (r(xy)). A multivariate regression was performed to identify the influence of NMR variables on sdLDL-C.Results A strong association between sdLDL-C and LDLLDL-P (r(xy) = 0.687) and with LDL-Z (r(xy) = -0.603) was found. The multivariate regression explained a 56.8% in sdLDL-C variation (P = 8.77.10-12). BMI, ApoB, triglycerides, FFA, and LDL-Z showed a significant contribution. The most important ones were ApoB and LDL-Z; a 1nm increase (LDL-Z) leads to decrease 126 nmol/L in sdLDL-C.Conclusion The association between sdLDL-C, LDL-Z, and LDL-P is clear. From a large number of variables, especially LDL-Z and apoB influence on sdLDL-C. Results show that the smaller the LDL size, the higher their cholesterol concentration. Therefore, sdLDL-C determination by using this easy method would be useful to risk stratification and to uncover cardiovascular residual risk.Background LDL-C lowering is the main measure in cardiovascular disease prevention but a residual risk of ischemic events still remains. Alterations of lipoproteins, specially, increase in small dense LDL (sdLDL) particles are related to this risk.Objective To investigate the potential use of sdLDL cholesterol concentration (sdLDL-C) isolated by an easy precipitation method and to assess the impact of a set of clinical and biochemical variables determined by NMR on sdLDL concentration.Methods sdLDL-C and NMR lipid profile were performed in 85 men samples. Association among them was evaluated using Pearson coefficients (r(xy)). A multivariate regression was performed to identify the influence of NMR variables on sdLDL-C.Results A strong association between sdLDL-C and LDLLDL-P (r(xy) = 0.687) and with LDL-Z (r(xy) = -0.603) was found. The multivariate regression explained a 56.8% in sdLDL-C variation (P = 8.77.10-12). BMI, ApoB, triglycerides, FFA, and LDL-Z showed a significant contribution. The most important ones were ApoB and LDL-Z; a 1nm increase (LDL-Z) leads to decrease 126 nmol/L in sdLDL-C.Conclusion The association between sdLDL-C, LDL-Z, and LDL-P is clear. From a large number of variables, especially LDL-Z and apoB influence on sdLDL-C. Results show that the smaller the LDL size, the higher their cholesterol concentration. Therefore, sdLDL-C determination by using this easy method would be useful to risk stratification and to uncover cardiovascular residual risk.

Statin therapy response is highly variable. Variants of lipid metabolism genes and statin pharmacokinetic modulators could play a role, however, the impact of most of these variants remains unconfirmed. A prospective and multicenter study included 252 patients was carried out in order to assess, according to achievement of LDL-C or non-HDL-C therapeutic targets and quantitative changes in lipid profiles, the impact of CETP, ABCA1, CYP2D6, and CYP2C9 gene candidate variants on the simvastatin, atorvastatin, and rosuvastatin response. Patients carrier ABCA1 rs2230806 and CYP2D6*3 variants are less likely to achieve therapeutic lipid targets (p = 0.020, OR = 0.59 [0.37, 0.93]; p = 0.040, OR = 0.23 [0.05, 0.93], respectively). Among CETP variants, rs708272 was linked to a 10.56% smaller reduction in LDL-C with rosuvastatin (95% CI = [1.27, 19.86] %; p = 0.028). In contrast, carriers of rs5882 had a 13.33% greater reduction in LDL-C (95% CI = [25.38, 1.28]; p = 0.032). If these findings are confirmed, ABCA1, CYP2D6, and CETP genotyping could be used to help predict which statin and dosage is appropriate in order to improve personalized medicine.