[Elderly benefit from lower LDL-cholesterol]. / Även hos äldre kan sänkt LDL ge minskad risk för hjärtsjukdom.

In two recent publications LDL-cholesterol and cardiovascular risk in the elderly was studied. A study from Copenhagen shows that LDL-cholesterol is similar as a risk-factor for myocardial infarction in all age-groups. Due to the higher incidence of myocardial infarction with age, the number of events associated with an increased LDL is higher among the elderly. The effect of LDL reduction in the elderly was studied in a meta-analysis including statin studies as well as studies with ezetimibe and PCSK9 inhibitors. The relative risk reduction associated with a reduction of 1 mmol/l of LDL-cholesterol was 26%, similar for patients above or below 75 years of age.  These studies emphasize that reduction of LDL should be considered also in the elderly without many comorbidities.

Virtual genetic diagnosis for familial hypercholesterolemia powered by machine learning.

AIMS: Familial hypercholesterolemia (FH) is the most common genetic disorder of lipid metabolism. The gold standard for FH diagnosis is genetic testing, available, however, only in selected university hospitals. Clinical scores - for example, the Dutch Lipid Score - are often employed as alternative, more accessible, albeit less accurate FH diagnostic tools. The aim of this study is to obtain a more reliable approach to FH diagnosis by a "virtual" genetic test using machine-learning approaches. METHODS AND RESULTS: We used three machine-learning algorithms (a classification tree (CT), a gradient boosting machine (GBM), a neural network (NN)) to predict the presence of FH-causative genetic mutations in two independent FH cohorts: the FH Gothenburg cohort (split into training data (N = 174) and internal test (N = 74)) and the FH-CEGP Milan cohort (external test, N = 364). By evaluating their area under the receiver operating characteristic (AUROC) curves, we found that the three machine-learning algorithms performed better (AUROC 0.79 (CT), 0.83 (GBM), and 0.83 (NN) on the Gothenburg cohort, and 0.70 (CT), 0.78 (GBM), and 0.76 (NN) on the Milan cohort) than the clinical Dutch Lipid Score (AUROC 0.68 and 0.64 on the Gothenburg and Milan cohorts, respectively) in predicting carriers of FH-causative mutations. CONCLUSION: In the diagnosis of FH-causative genetic mutations, all three machine-learning approaches we have tested outperform the Dutch Lipid Score, which is the clinical standard. We expect these machine-learning algorithms to provide the tools to implement a virtual genetic test of FH. These tools might prove particularly important for lipid clinics without access to genetic testing.

Quantifying atherogenic lipoproteins for lipid-lowering strategies: Consensus-based recommendations from EAS and EFLM.

The joint consensus panel of the European Atherosclerosis Society (EAS) and the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) recently addressed present and future challenges in the laboratory diagnostics of atherogenic lipoproteins. Total cholesterol, triglycerides, HDL cholesterol, LDL cholesterol, and calculated non-HDL cholesterol (=total - HDL cholesterol) constitute the primary lipid panel for estimating risk of atherosclerotic cardiovascular disease (ASCVD) and can be measured in the nonfasting state. LDL cholesterol is the primary target of lipid-lowering therapies. For on-treatment follow-up, LDL cholesterol shall be measured or calculated by the same method to attenuate errors in treatment decisions due to marked between-method variations. Lipoprotein(a)-cholesterol is part of measured or calculated LDL cholesterol and should be estimated at least once in all patients at risk of ASCVD, especially in those whose LDL cholesterol decline poorly upon statin treatment. Residual risk of ASCVD even under optimal LDL-lowering treatment should be also assessed by non-HDL cholesterol or apolipoprotein B, especially in patients with mild-to-moderate hypertriglyceridemia (2-10 mmol/L). Non-HDL cholesterol includes the assessment of remnant lipoprotein cholesterol and shall be reported in all standard lipid panels. Additional apolipoprotein B measurement can detect elevated LDL particle numbers often unidentified on the basis of LDL cholesterol alone. Reference intervals of lipids, lipoproteins, and apolipoproteins are reported for European men and women aged 20-100 years. However, laboratories shall flag abnormal lipid values with reference to therapeutic decision thresholds.

Quantifying atherogenic lipoproteins for lipid-lowering strategies: consensus-based recommendations from EAS and EFLM.

The joint consensus panel of the European Atherosclerosis Society (EAS) and the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) recently addressed present and future challenges in the laboratory diagnostics of atherogenic lipoproteins. Total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDLC), LDL cholesterol (LDLC), and calculated non-HDLC (=total - HDLC) constitute the primary lipid panel for estimating risk of atherosclerotic cardiovascular disease (ASCVD) and can be measured in the nonfasting state. LDLC is the primary target of lipid-lowering therapies. For on-treatment follow-up, LDLC shall be measured or calculated by the same method to attenuate errors in treatment decisions due to marked between-method variations. Lipoprotein(a) [Lp(a)]-cholesterol is part of measured or calculated LDLC and should be estimated at least once in all patients at risk of ASCVD, especially in those whose LDLC declines poorly upon statin treatment. Residual risk of ASCVD even under optimal LDL-lowering treatment should be also assessed by non-HDLC or apolipoprotein B (apoB), especially in patients with mild-to-moderate hypertriglyceridemia (2-10 mmol/L). Non-HDLC includes the assessment of remnant lipoprotein cholesterol and shall be reported in all standard lipid panels. Additional apoB measurement can detect elevated LDL particle (LDLP) numbers often unidentified on the basis of LDLC alone. Reference intervals of lipids, lipoproteins, and apolipoproteins are reported for European men and women aged 20-100 years. However, laboratories shall flag abnormal lipid values with reference to therapeutic decision thresholds.

Understanding the Patient Perception of Statin Experience: A Qualitative Study.

INTRODUCTION: Statin intolerance (SI) occurs in patients with dyslipidemia treated with statins. Statin-associated symptoms have been reported, but the overall patient experience is poorly understood. No instruments are available to collect this patient experience. Our aim is to develop a patient survey to define SI from the patient's perspective, inform clinical practice, and identify potential patient characteristics and barriers associated with discontinuing treatment when statin-related difficulties are encountered. METHODS: We conducted qualitative concept elicitation interviews with 65 patients across 12 European study sites. A semi-structured qualitative interview guide was developed based on literature review and clinician interviews. Concept elicitation interviews with patients were used to describe the patient experience and develop the conceptual framework for the survey. RESULTS: Symptoms experienced by patients included muscle and non-muscle-related pain and discomfort; other muscle-related symptoms; gastrointestinal, cardiovascular, cold-like, fatigue-related, and sensory and systems symptoms; mood changes; and cognitive and memory problems. Impacts included limitations on general physical functioning; physical activities; social functioning; emotional impacts; sleep disturbances; decreased productivity; and increased healthcare use. Conceptual framework elements to support survey goals include demographic and clinical characteristics, health information and beliefs, statin side-effect history, symptom severity, and impact severity. CONCLUSIONS: Symptoms and impacts described by patients showed a wider range of symptoms and impacts than usually discussed clinically. The patient survey is designed to capture information from patients who experience difficulties with statin therapy and may be useful in identifying patients who are at higher risk for giving up or discontinuing their treatment. FUNDING: Amgen Inc.

High prevalence of genetic determined familial hypercholesterolemia in premature coronary artery disease.

Background: Premature coronary artery disease (CAD) is a major cause of mortality and morbidity. Increased low-density lipoprotein-cholesterol (LDL-C) level is a major risk factor for CAD and thus the main target for its prevention. Familial Hypercholesterolemia (FH) is a genetic inherited disorder characterized by high LDL-C, and subsequent premature CAD development. Early drug treatment with lipid-lowering medications in FH prevents cardiovascular disease onset. The FH prevalence in the Northern European general population is 0.3%, and it is estimated that it explains 20% of premature CAD cases in individuals with familial clustering. Despite the wide number of papers showing the prevalence of clinical FH in cardiovascular disease, the prevalence of genetic FH in individuals with premature CAD is not yet well known. Here, we examined the prevalence of genetically determined FH in individuals with premature CAD. Patients and methods: 66 patients who underwent coronary angiography with suspected premature acute coronary syndrome (age <50 years for men and <55 years for women) underwent genetic screening to identify FH-causing mutations. All patients underwent physical and clinical examinations. Information about family and personal history, drug therapy and habits were also collected. Results: We found FH-causative mutations in 3/66 (4.5%) screened individuals with premature CAD. When considering individuals with confirmed CAD after coronary angiography, the FH mutation prevalence was 6.1% (3/49). After excluding individuals with classical risk factors for CAD other than hypercholesterolemia, the FH mutation prevalence raised to 15.8% (3/19). Conclusion: In conclusion, we found that individuals with premature CAD have a more than 15-fold increased prevalence of FH mutations compared to the general population.

Quantifying Atherogenic Lipoproteins: Current and Future Challenges in the Era of Personalized Medicine and Very Low Concentrations of LDL Cholesterol. A Consensus Statement from EAS and EFLM.

BACKGROUND: The European Atherosclerosis Society-European Federation of Clinical Chemistry and Laboratory Medicine Consensus Panel aims to provide recommendations to optimize atherogenic lipoprotein quantification for cardiovascular risk management. CONTENT: We critically examined LDL cholesterol, non-HDL cholesterol, apolipoprotein B (apoB), and LDL particle number assays based on key criteria for medical application of biomarkers. (a) Analytical performance: Discordant LDL cholesterol quantification occurs when LDL cholesterol is measured or calculated with different assays, especially in patients with hypertriglyceridemia >175 mg/dL (2 mmol/L) and low LDL cholesterol concentrations <70 mg/dL (1.8 mmol/L). Increased lipoprotein(a) should be excluded in patients not achieving LDL cholesterol goals with treatment. Non-HDL cholesterol includes the atherogenic risk component of remnant cholesterol and can be calculated in a standard nonfasting lipid panel without additional expense. ApoB more accurately reflects LDL particle number. (b) Clinical performance: LDL cholesterol, non-HDL cholesterol, and apoB are comparable predictors of cardiovascular events in prospective population studies and clinical trials; however, discordance analysis of the markers improves risk prediction by adding remnant cholesterol (included in non-HDL cholesterol) and LDL particle number (with apoB) risk components to LDL cholesterol testing. (c) Clinical and cost-effectiveness: There is no consistent evidence yet that non-HDL cholesterol-, apoB-, or LDL particle-targeted treatment reduces the number of cardiovascular events and healthcare-related costs than treatment targeted to LDL cholesterol. SUMMARY: Follow-up of pre- and on-treatment (measured or calculated) LDL cholesterol concentration in a patient should ideally be performed with the same documented test method. Non-HDL cholesterol (or apoB) should be the secondary treatment target in patients with mild to moderate hypertriglyceridemia, in whom LDL cholesterol measurement or calculation is less accurate and often less predictive of cardiovascular risk. Laboratories should report non-HDL cholesterol in all standard lipid panels.

Adverse effects of statin therapy: perception vs. the evidence - focus on glucose homeostasis, cognitive, renal and hepatic function, haemorrhagic stroke and cataract.

Aims: To objectively appraise evidence for possible adverse effects of long-term statin therapy on glucose homeostasis, cognitive, renal and hepatic function, and risk for haemorrhagic stroke or cataract. Methods and results: A literature search covering 2000-2017 was performed. The Panel critically appraised the data and agreed by consensus on the categorization of reported adverse effects. Randomized controlled trials (RCTs) and genetic studies show that statin therapy is associated with a modest increase in the risk of new-onset diabetes mellitus (about one per thousand patient-years), generally defined by laboratory findings (glycated haemoglobin ≥6.5); this risk is significantly higher in the metabolic syndrome or prediabetes. Statin treatment does not adversely affect cognitive function, even at very low levels of low-density lipoprotein cholesterol and is not associated with clinically significant deterioration of renal function, or development of cataract. Transient increases in liver enzymes occur in 0.5-2% of patients taking statins but are not clinically relevant; idiosyncratic liver injury due to statins is very rare and causality difficult to prove. The evidence base does not support an increased risk of haemorrhagic stroke in individuals without cerebrovascular disease; a small increase in risk was suggested by the Stroke Prevention by Aggressive Reduction of Cholesterol Levels study in subjects with prior stroke but has not been confirmed in the substantive evidence base of RCTs, cohort studies and case-control studies. Conclusion: Long-term statin treatment is remarkably safe with a low risk of clinically relevant adverse effects as defined above; statin-associated muscle symptoms were discussed in a previous Consensus Statement. Importantly, the established cardiovascular benefits of statin therapy far outweigh the risk of adverse effects.

New strategies for the development of lipid-lowering therapies to reduce cardiovascular risk.

The very high occurrence of cardiovascular events presents a major public health issue, because treatment remains suboptimal. Lowering LDL cholesterol (LDL-C) with statins or ezetimibe in combination with a statin reduces major adverse cardiovascular events. The cardiovascular risk reduction in relation to the absolute LDL-C reduction is linear for most interventions without evidence of attenuation or increase in risk at low LDL-C levels. Opportunities for innovation in dyslipidaemia treatment should address the substantial risk of lipid-associated cardiovascular events among patients optimally treated per guidelines but who cannot achieve LDL-C goals and who could benefit from additional LDL-C-lowering therapy or experience side effects of statins. Fresh approaches are needed to identify promising drug targets early and develop them efficiently. The Cardiovascular Round Table of the European Society of Cardiology (ESC) convened a workshop to discuss new lipid-lowering strategies for cardiovascular risk reduction. Opportunities to improve treatment approaches and the efficient study of new therapies were explored. Circulating biomarkers may not be fully reliable proxy indicators of the relationship between treatment effect and clinical outcome. Mendelian randomization studies may better inform development strategies and refine treatment targets before Phase 3. Trials should match the drug to appropriate lipid and patient profile, and guidelines may move towards a precision-based approach to individual patient management. Stakeholder collaboration is needed to ensure continued innovation and better international coordination of both regulatory aspects and guidelines. It should be noted that risk may also be addressed through increased attention to other risk factors such as smoking, hypertension, overweight, and inactivity.

Low-density lipoproteins cause atherosclerotic cardiovascular disease. 1. Evidence from genetic, epidemiologic, and clinical studies. A consensus statement from the European Atherosclerosis Society Consensus Panel.

AIMS: To appraise the clinical and genetic evidence that low-density lipoproteins (LDLs) cause atherosclerotic cardiovascular disease (ASCVD). METHODS AND RESULTS: We assessed whether the association between LDL and ASCVD fulfils the criteria for causality by evaluating the totality of evidence from genetic studies, prospective epidemiologic cohort studies, Mendelian randomization studies, and randomized trials of LDL-lowering therapies. In clinical studies, plasma LDL burden is usually estimated by determination of plasma LDL cholesterol level (LDL-C). Rare genetic mutations that cause reduced LDL receptor function lead to markedly higher LDL-C and a dose-dependent increase in the risk of ASCVD, whereas rare variants leading to lower LDL-C are associated with a correspondingly lower risk of ASCVD. Separate meta-analyses of over 200 prospective cohort studies, Mendelian randomization studies, and randomized trials including more than 2 million participants with over 20 million person-years of follow-up and over 150 000 cardiovascular events demonstrate a remarkably consistent dose-dependent log-linear association between the absolute magnitude of exposure of the vasculature to LDL-C and the risk of ASCVD; and this effect appears to increase with increasing duration of exposure to LDL-C. Both the naturally randomized genetic studies and the randomized intervention trials consistently demonstrate that any mechanism of lowering plasma LDL particle concentration should reduce the risk of ASCVD events proportional to the absolute reduction in LDL-C and the cumulative duration of exposure to lower LDL-C, provided that the achieved reduction in LDL-C is concordant with the reduction in LDL particle number and that there are no competing deleterious off-target effects. CONCLUSION: Consistent evidence from numerous and multiple different types of clinical and genetic studies unequivocally establishes that LDL causes ASCVD.

PNPLA3 overexpression results in reduction of proteins predisposing to fibrosis.

Liver fibrosis is a pathological scarring response to chronic hepatocellular injury and hepatic stellate cells (HSCs) are key players in this process. PNPLA3 I148M is a common variant robustly associated with liver fibrosis but the mechanisms underlying this association are unknown. We aimed to examine a) the effect of fibrogenic and proliferative stimuli on PNPLA3 levels in HSCs and b) the role of wild type and mutant PNPLA3 overexpression on markers of HSC activation and fibrosis.Here, we show that PNPLA3 is upregulated by the fibrogenic cytokine transforming growth factor-beta (TGF-ß), but not by platelet-derived growth factor (PDGF), and is involved in the TGF-ß-induced reduction in lipid droplets in primary human HSCs. Furthermore, we show that retinol release from human HSCs ex vivo is lower in cells with the loss-of-function PNPLA3 148M compared with 148I wild type protein. Stable overexpression of PNPLA3 148I wild type, but not 148M mutant, in human HSCs (LX-2 cells) induces a reduction in the secretion of matrix metallopeptidase 2 (MMP2), tissue inhibitor of metalloproteinase 1 and 2 (TIMP1 and TIMP2), which is mediated by retinoid metabolism. In conclusion, we show a role for PNPLA3 in HSC activation in response to fibrogenic stimuli. Moreover, we provide evidence to indicate that PNPLA3-mediated retinol release may protect against liver fibrosis by inducing a specific signature of proteins involved in extracellular matrix remodelling.