Secondary findings from whole-exome sequencing data in families with familial combined hyperlipidemia (FCHL)

Background During the interpretation of genome sequencing data, some types of secondary findings are identified that are located in genes that do not appear to be related to the causes of the primary disease. Although these are not the primary targets for evaluation, they have a high risk for some diseases different from the primary disease. Therefore, they can be vital for preventing and intervention from such disease. Results Here, we analyzed secondary findings obtained from WES in 6 families with FCHL disease who had an autosomal-dominant pattern based on their pedigrees. These finding are found in CDKAL1, ITGA2, FAM111A, WNK4, PTGIS, SCN10, TBX20, DCHS1, ANK2 and ABCA1 genes. Conclusions Secondary findings are very important and must be considered different variants from sequencing results in a diagnostic setting. Although we have considered these variants as secondary findings, some of them may be related to the primary disease.

Carotid Artery Temperature Reduction with Statin Therapy in Patients with Familial Hyperlipidemia Syndromes

Background: Microwave radiometry (MWR) assesses non-invasive carotid artery temperatures reflecting inflammation. In the present study, we aimed to investigate the impact of hypolipidemic therapy either with simvastatin or with combination simvastatin plus ezetimibe on carotid artery temperatures of patients with familial hyperlipidemia syndromes (FHS). Methods: Consecutive patients with diagnosis of either familial heterozygous hypercholesterolemia (heFH) or familial combined hyperlipidemia (FCH) were included in the study. Patients were assigned to either simvastatin 40 mg or simvastatin 40 mg plus ezetimibe 10 mg, according to the discretion of the physician. FHS patients who refused statin therapy were used as a control group. Common carotid intima-media thickness (ccIMT) was measured and ΔΤ (maximum-minimum) temperature measurements were performed across each carotid during MWR evaluation. RESULTS: In total, 115 patients were included in the study. Of them, 40 patients received simvastatin (19 heFH and 21 FCH), 41 simvastatin + ezetimibe (31 heFH and 10 FCH), and 34 (21 heFH and 13 FCH) no statin. Carotid artery temperatures were significantly reduced at 6 months in FH patients who received hypolipidemic treatment (0.83 ± 0.34 versus 0.63 ± 0.24 oC, p = 0.004 for simvastatin, 1.00 ± 0.38 versus 0.69 ± 0.23 oC, p < 0.001 for simvastatin+ezetimibe), but no change was recorded in controls (0.72 ± 0.26 versus 0.70 ± 0.26 oC, p = 0.86). CONCLUSIONS: Hypolipidemic therapy reduced carotid temperatures in FHS patients.

Familial combined hyperlipidemia: current knowledge about pathophysiology, diagnostics and correction

The review is devoted to the current knowledge about pathophysiology, diagnostics and correction of familial combined hyperlipidemia (FCHL) that is considered to be the most frequent among primary dyslipidemias in general population (1 — 3 %) as well as among the patients survived after myocardial infarction (20 — 38 %). The current knowledge about genetic characterization of FCHL and its pathophysiology are adduced. FCHL is emphasized to be a heterogenic state and many of genetic determinants are involved in its development. Excessive concentration of apolipoprotein B (ApoB) — containing lipoproteins is shown to be the main biochemical sign of FCHL and hence, the genes of proteins participated in their metabolism could be claimed for genes‑candidates of FCHL. A special attention is paid to the diagnostics of FCHL, the most valuable diagnostic signs of FCHL are emphasized because FCHL is not monogenic disorder and due to its phenotype characterized by high levels of low‑density lipoprotein cholesterol and/or triglyceride (TG), this lipid disorder is not frequently diagnosed. A combination of concentrations of ApoB > 120 mg/dl and TG > 1.5 mmol/l (> 133 mg/dl) with a family history of early cardiovascular debut could be used today for revelation of patients with a probable diagnosis of FCHL. The influence of FCHL on cardiovascular risk (CVR) that is partly realized through its association with metabolic comorbid conditions such as type 2 diabetes mellitus, metabolic syndrome, nonalcoholic fatty liver disease is considered. These comorbid conditions could play a role of etiological causes of cardiovascular disease and could increase a CVR through some common pathophysiological mechanisms such as insulin resistance of muscular and fat tissues and hepatic overproduction of very low‑density lipoproteins. The current approaches to FCHL correction in accordance with acting recommendations are elucidated. They consider its correction to be necessary as a primary atherogenic dyslipidemia and propose to start intervention from the influence on modified factors of CVR (smoking, alcohol consumption, excessive body mass, obesity). Some differential approaches to correction of lipid exchange disorders in FCHL from the beginning of the first line hypolipidemic agent (statin of fibrate) or their combined usage depended on dyslipidemia phenotype revealed during diagnostics of FCHL are discussed. Update combinations of hypolipidemic agents with an addition to statin and fibrate omega‑3 fatty acids, ezetimibe and inhibitors of PCSK9 (alirocumab, evolocumab) from the point of their influence on a reduction of CVR as well as on the components of dyslipidemia phenotype occurred in FCHL are considered.

ANGPTL3 gene variants in subjects with familial combined hyperlipidemia

Angiopoietin-like 3 (ANGPTL3) plays an important role in lipid metabolism in humans. Loss-of-function variants in ANGPTL3 cause a monogenic disease named familial combined hypolipidemia. However, the potential contribution of ANGPTL3 gene in subjects with familial combined hyperlipidemia (FCHL) has not been studied. For that reason, the aim of this work was to investigate the potential contribution of ANGPTL3 in the aetiology of FCHL by identifying gain-of-function (GOF) genetic variants in the ANGPTL3 gene in FCHL subjects. ANGPTL3 gene was sequenced in 162 unrelated subjects with severe FCHL and 165 normolipemic controls. Pathogenicity of genetic variants was predicted with PredictSNP2 and FruitFly. Frequency of identified variants in FCHL was compared with that of normolipemic controls and that described in the 1000 Genomes Project. No GOF mutations in ANGPTL3 were present in subjects with FCHL. Four variants were identified in FCHL subjects, showing a different frequency from that observed in normolipemic controls: c.607-109T>C, c.607-47_607-46delGT, c.835+41C>A and c.*52_*60del. This last variant, c.*52_*60del, is a microRNA associated sequence in the 3′UTR of ANGPTL3, and it was present 2.7 times more frequently in normolipemic controls than in FCHL subjects. Our research shows that no GOF mutations in ANGPTL3 were found in a large group of unrelated subjects with FCHL.

Comparative assessment of LDL-C and VLDL-C estimation in Familial Combined Hyperlipidemia using Sampson’s, Martin’s and Friedewald’s equations

Background: Sampson et al developed a novel method to estimate very low-density lipoprotein cholesterol (VLDL-C) and low-density lipoprotein cholesterol (LDL-C) in the setting of hypertriglyceridemia. Familial Combined Hyperlipidemia (FCHL) is a common primary dyslipidemia in which lipoprotein composition interferes with LDL-C estimation. This study aimed to evaluate performance of LDL-C using this new method (LDL-S) compared with LDL-C estimated by Friedewald’s and Martin equation (LDL-F, LDL-M) in FCHL.Methods: Data were collected from 340 subjects with confirmed FCHL. Concordance for VLDL-C measured by ultracentrifugation and LDL-C estimated using these measures compared to Sampson’s, Martin’s and Friedewald’s equations was performed using correlation coefficients, root mean squared error (RMSE) and bias. We also assessed concordance of misclassified metrics according to LDL-C (<70 and <100mg/dL) and ApoB (<80 and <65mg/dL) thresholds.Results: Sampson’s equation was more accurate (RMSE 11.21 mg/dL; R2=0.88) compared to Martin’s (RMSE 13.15 mg/dL; R2=0.875) and the Friedewald equation (RMSE 13.7 mg/dL; R2= 0.869). When assessing performance according to LDL-C, Sampson’s had highest correlation and lowest RMSE compared to other equations (RMSE 19.99 mg/dL; R2=0.840). Comparing performance strength across triglyceride levels, Sampson’s showed consistently improved correlations compared to Martin’s and Friedewald’s formulas for increasing triglycerides and for the FCHL phenotype of mixed dyslipidemia. Sampson’s also had improved concordance with treatment goals.Conclusions: In FCHL, VLDL-C and LDL-C estimation using Sampson’s formula showed higher concordance with lipid targets assessed using VLDL-C obtained by ultracentrifugation compared with Friedewald’s and Martin’s equations. Implementation of Sampson’s formula could improve treatment monitoring in FCHL.

Comparative Assessment of LDL-C and VLDL-C Estimation in Familial Combined Hyperlipidemia using Sampson’s, Martin’s and Friedewald’s Equations.

Background: Sampson et al developed a novel method to estimate very low-density lipoprotein cholesterol (VLDL-C) and low-density lipoprotein cholesterol (LDL-C) in the setting of hypertriglyceridemia. Familial Combined Hyperlipidemia (FCHL) is a common primary dyslipidemia in which lipoprotein composition interferes with LDL-C estimation. This study aimed to evaluate performance of LDL-C using this new method (LDL-S) compared with LDL-C estimated by Friedewald’s and Martin equation (LDL-F, LDL-M) in FCHL.Methods: Data were collected from 340 subjects with confirmed FCHL. Concordance for VLDL-C measured by ultracentrifugation and LDL-C estimated using these measures compared to Sampson’s, Martin’s and Friedewald’s equations was performed using correlation coefficients, root mean squared error (RMSE) and bias. We also assessed concordance of misclassified metrics according to LDL-C (<70 and <100mg/dL) and ApoB (<80 and <65mg/dL) thresholds.Results: Sampson’s equation was more accurate (RMSE 11.21 mg/dL; R2=0.88) compared to Martin’s (RMSE 13.15 mg/dL; R2=0.875) and the Friedewald equation (RMSE 13.7 mg/dL; R2= 0.869). When assessing performance according to LDL-C, Sampson’s had highest correlation and lowest RMSE compared to other equations (RMSE 19.99 mg/dL; R2=0.840). Comparing performance strength across triglyceride levels, Sampson’s showed consistently improved correlations compared to Martin’s and Friedewald’s formulas for increasing triglycerides and for the FCHL phenotype of mixed dyslipidemia. Sampson’s also had improved concordance with treatment goals.Conclusions: In FCHL, VLDL-C and LDL-C estimation using Sampson’s formula showed higher concordance with lipid targets assessed using VLDL-C obtained by ultracentrifugation compared with Friedewald’s and Martin’s equations. Implementation of Sampson’s formula could improve treatment monitoring in FCHL.