Simon Broome Criteria Research Articles

Clinical and genetic diagnosis of familial hypercholesterolaemia in patients undergoing coronary angiography: the Ludwigshafen Risk and Cardiovascular Health Study.

To investigate the prevalence of familial hypercholesterolaemia (FH) and compare the performance of clinical criteria and genetic testing in patients undergoing coronary angiography. The prevalence of FH was determined with the Dutch Lipid Clinical Network (DLCN), US-MEDPED, Simon Broome (SB) criteria, the 'Familial Hypercholesterolaemia Case Ascertainment Tool' (FAMCAT), and a clinical algorithm. Genetic screening was conducted with a custom array from Affymetrix (CARRENAL array) harboring 944 FH mutations. The study cohort consisted of 3267 patients (78.6% with coronary artery disease [CAD]). FH was diagnosed in 2.8%, 2.2%, 3.9%, and 7.9% using the DLCN, US-MEDPED, SB criteria, and the FAMCAT. The clinical algorithm identified the same patients as the SB criteria. Pathogenic FH mutations were found in 1.2% (1.2% in patients with CAD, 1.0% in patients without CAD). FH was more frequently diagnosed in younger patients. With genetic testing as reference, the clinical criteria achieved areas under the ROC curve (AUCs) in the range of 0.56-0.68. Using only LDL-C corrected for statin intake, an AUC of 0.68 was achieved. FH is up to fourfold more prevalent in patients undergoing coronary angiography than in contemporary cohorts representing the general population. Different clinical criteria yield substantially different diagnosis rates, overestimating the prevalence of FH compared to genetic testing. LDL-C testing alone may be sufficient to raise the suspicion of FH, which then needs to be corroborated by genetic testing.

Clinical characteristics of carriers of pathogenic LDLR and АРОВ mutations

Aim. To analyze the clinical characteristics of carriers of pathogenic LDLR and АРОВ mutations, as well as the prognostic value of Dutch Lipid Clinic Network Score (DLCNS) as applied to carriage of АРОВ or LDLR.Material and methods. The study included 1233 outpatient lipid clinic patients. Biomaterial samples from 421 patients with the hereditary dyslipidemia were studied using Next Generation Sequencing (NGS) to identify carriage of familial hypercholesterolemia (FH)-associated genes (LDLR, АРОВ, PCSK9, LDLRAP1), as well as polymorphism of the APOE gene. Statistical processing was performed using descriptive statistics methods.Results. According to the data obtained, the most significant predictors of pathogenic LDLR mutations are the levels of total cholesterol, low-density lipoprotein cholesterol (LDL-C), family history of coronary artery disease (CAD), and previous coronary artery bypass grafting. The level of LDL-C, family history of cerebrovascular accident or CAD, and arcus senilis were more significant for verifying the carriage of pathogenic АРОВ mutations. Using screening potential carriers of FH using the DLCN or Simon-Broome diagnostic criteria, the probability of FH may be underestimated due to the discrepancy between the scale criteria and the prognostic contribution of clinical or anamnestic data. These scales do not take into account the estrogen status of potential female carriers of FH.Conclusion. Thus, diagnostic criteria for identifying potential FH vary among different patient groups. Their diagnostic significance depends on sex, and in women, on reproductive status. Only part of DLCN and Simon-Broome criteria can be applied to assess the FH likelihood, and to a greater extent for carriage of LDLR, but not АРОВ.

Comparative study on the performance of different classification algorithms, combined with pre- and post-processing techniques to handle imbalanced data, in the diagnosis of adult patients with familial hypercholesterolemia.

Familial Hypercholesterolemia (FH) is an inherited disorder of cholesterol metabolism. Current criteria for FH diagnosis, like Simon Broome (SB) criteria, lead to high false positive rates. The aim of this work was to explore alternative classification procedures for FH diagnosis, based on different biological and biochemical indicators. For this purpose, logistic regression (LR), naive Bayes classifier (NB), random forest (RF) and extreme gradient boosting (XGB) algorithms were combined with Synthetic Minority Oversampling Technique (SMOTE), or threshold adjustment by maximizing Youden index (YI), and compared. Data was tested through a 10 × 10 repeated k-fold cross validation design. The LR model presented an overall better performance, as assessed by the areas under the receiver operating characteristics (AUROC) and precision-recall (AUPRC) curves, and several operating characteristics (OC), regardless of the strategy to cope with class imbalance. When adopting either data processing technique, significantly higher accuracy (Acc), G-mean and F1 score values were found for all classification algorithms, compared to SB criteria (p < 0.01), revealing a more balanced predictive ability for both classes, and higher effectiveness in classifying FH patients. Adjustment of the cut-off values through pre or post-processing methods revealed a considerable gain in sensitivity (Sens) values (p < 0.01). Although the performance of pre and post-processing strategies was similar, SMOTE does not cause model’s parameters to loose interpretability. These results suggest a LR model combined with SMOTE can be an optimal approach to be used as a widespread screening tool.

Comparing the performance of the novel FAMCAT algorithms and established case-finding criteria for familial hypercholesterolaemia in primary care

ObjectiveFamilial hypercholesterolaemia (FH) is a common inherited disorder causing premature coronary heart disease (CHD) and death. We have developed the novel Familial Hypercholesterolaemia Case Ascertainment Tool (FAMCAT 1) case-finding algorithm...

SEX DISPARITIES IN THE TREATMENT AND OUTCOMES OF FAMILIAL HYPERCHOLESTEROLEMIA

<h3>BACKGROUND</h3> Familial hypercholesterolemia (FH), an inherited condition equally prevalent in males and females, is characterized by elevated low-density lipoprotein cholesterol (LDL-C) in the blood. If left untreated, FH leads to the development of premature atherosclerotic cardiovascular disease (ASCVD) and death. Many barriers to care in FH exist, which can result in low rates of diagnosis and suboptimal treatment and outcomes. Sex disparities have been identified as an important barrier to care in CVD, however their influence on treatment and lipid target achievement in FH remains to be explored. <h3>METHODS AND RESULTS</h3> Here we performed a longitudinal registry analysis of sex differences in treatment and lipid level achievement in Heterozygous FH (HeFH) patients at the MUHC. Patients were included in the study if they were diagnosed as either "definite", "probable", or "possible" FH based on the Simon-Broome criteria, Dutch Lipid Clinic Network criteria, or the new Canadian FH definition. Differences between males and females were calculated using a t-test or chi-squared test. There were 127 females and 162 males from the McGill FH Registry included in the analysis. The mean age at the initial clinic visit was 49±17 years for females and 45±16 years for males (p=0.04). First, we analyzed sex differences in lipid lowering medication use. At the most recent clinic visit, there were more males (89%) than females (76%) taking statins (p=0.7), and only 35% of females were on high-intensity statins, compared to 74% of males (p=0.002). Interestingly, statin intolerance was reported in 40% of females and 22% of males (p=0.02). We then examined guideline-recommended lipid target achievement between both sexes. At baseline, males and females had similar mean LDL-C levels of 6.9±2.2 mmol/L and 6.7±1.6 mmol/L respectively (p=0.7). Despite this, at the most recent visit, 55% of males reached a target LDL-C of ≤ 2.5 mmol/L compared to just 32% of females (p=0.02). As well, from baseline to most recent visit, females reduced their LDL-C by 51%, whereas males lowered their LDL-C by 62% (p=0.01). Thus, fewer females are reaching appropriate guideline-based target LDL-C levels compared to males. <h3>CONCLUSION</h3> Our analysis reveals a sex bias in FH patients in favour of males in regard to treatment intensity and lipid level target achievement. Identifying these imbalances will allow us to break down these barriers in care through educational initiatives and additional training, to improve quality of life and life expectancy of individuals with FH.

The Use of Genetic Testing Panels for Dyslipidemia: A Quality Improvement Project at the McGill University Health Centre

Background: Genetic testing panels are used to identify the most common genetic causes of dyslipidemia, and the results of these panels can guide treatment and management. The objective of this quality improvement project was to assess the appropriateness of genetic testing panels requested by the McGill University Health Centre (MUHC). Methods: Genetic testing panels sent for analysis from January 2018 to December 2019 were identified. Ordering physician specialty, patient personal and family medical history, lipid panel results, and genetic testing results were collected. Then, validated Familial Hyperlipidemia (FH) scores (Simon-Broome Registry Criteria, Dutch Lipid Clinic Network Criteria, FH Canada criteria) were calculated for patients who underwent genetic testing for suspected FH. Results: There were 36 genetic test panels sent out for analysis during the study period, of which 24 were accessible for data analysis. Pathogenic mutations were identified in 7/24 (29%) of the analyzed panels. The 19/24 (79%) of the panels were requested by lipid specialists, and all of the panels positive for pathogenic mutations were requested by lipid specialists. Interestingly, 23/24 (94%) of the patients met the Canadian criteria for at least considering genetic testing, suggesting that most panels were appropriately requested. Only 3/24 (12%) of patients had insufficient criteria for FH by the Simon-Broome criteria, but all of these carried pathogenic mutations. Conclusion: These results suggest that at the MUHC, using the Canadian criteria identifies a greater number of patients for genetic testing and for appropriate diagnosis and treatment.

Systematic Identification of Familial Hypercholesterolaemia in Primary Care-A Systematic Review.

Familial hypercholesterolaemia (FH) is a common inherited cause of premature cardiovascular disease, but the majority of patients remain undiagnosed. The aim of this systematic review was to assess the effectiveness of interventions to systematically identify FH in primary care. No randomised, controlled studies were identified; however, three non-randomised intervention studies were eligible for inclusion. All three studies systematically identified FH using reminders (on-screen prompts) in electronic health records. There was insufficient evidence that providing comments on laboratory test results increased the identification of FH using the Dutch Lipid Clinic Network (DLCN) criteria. Similarly, using prompts combined with postal invitation demonstrated no significant increase in definite FH identification using Simon-Broome (SB) criteria; however, the identification of possible FH increased by 25.4% (CI 17.75 to 33.97%). Using on-screen prompts alone demonstrated a small increase of 0.05% (95% CI 0.03 to 0.07%) in identifying definite FH using SB criteria; however, when the intervention was combined with an outreach FH nurse assessment, the result was no significant increase in FH identification using a combination of SB and DLCN criteria. None of the included studies reported adverse effects associated with the interventions. Currently, there is insufficient evidence to determine which is the most effective method of systematically identifying FH in non-specialist settings.

Abstract 16143: A Novel Clinical Prediction Model for Familial Hypercholesterolemia: Implementation of a Statin-correction Calculator to Enhance Diagnostic Yield

Introduction: Familial hypercholesterolemia (FH) is an autosomal dominant genetic disorder. Individuals with FH have a 22-fold greater risk of early-onset cardiovascular disease as compared to the general population. Early identification of patients with FH is essential to prevent cardiovascular events. Diagnosis may be challenging however for individuals with underlying FH who are already receiving statin therapy, as criteria for FH rely on pre-treatment low-density lipoprotein (LDL) levels. We calculated pre-treatment LDL levels utilizing prior published literature by adjusting for serum LDL levels in patients receiving statins. This increased the diagnostic yield for gene-positive FH. Hypothesis: Integration of statin-correction calculator with the Dutch Lipid Clinical Criteria (DLCC) and Simon Broome Criteria (SBC) for FH will increase sensitivity to identify gene-positive FH. Methods: 29,797 participants enrolled in the Healthy Nevada Project underwent whole-exome gene testing. 126 had a FH variant; 37 of these participants were on statin therapy. A statin-correction calculator was utilized to predict patients' pre-treatment LDL levels. The likelihood of FH was assessed based on two versions of the DLCC and SBC: the standard versions and enhanced versions with integration of the statin-correction calculator (eDLCC and eSBC). The McNemar test was used to compare the sensitivity of DLCC and SBC with eDLCC and eSBC, respectively, in identifying gene-positive FH. Results: By adjusting LDL levels for statin usage, 70.24% and 24.32% of participants with a negative diagnosis of FH were reclassified to positive using eDLCC and eSBC (p=0.001 and 0.008, respectively). Conclusions: Integration of statin-correction calculator to correct LDL increases diagnostic yield for clinical FH.

Effect of Lipoprotein(a) on the Diagnosis of Familial Hypercholesterolemia: Does It Make a Difference in the Clinic?

Diagnostic tools for familial hypercholesterolemia (FH) rely on estimation of LDL cholesterol concentration. However, routine measurement or calculation of LDL cholesterol concentration using the Friedewald equation contains a cholesterol contribution from lipoprotein(a) [Lp(a)]. We investigated whether Lp(a) influences the phenotypic diagnosis of FH by commonly used clinical criteria. A cohort of 907 adult index patients attending a clinic were studied. The Dutch Lipid Clinic Network (DLCN) and Simon Broome (SB) diagnostic criteria were estimated before and after adjusting LDL cholesterol concentration for the cholesterol content (30%) of Lp(a). Diagnostic reclassification rates and area under the ROC (AUROC) curves in predicting an FH mutation were also compared. Seventy-four patients defined by DLCN criteria (8.2%) and 207 patients defined by SB criteria (22.8%) were reclassified to "unlikely" FH after adjusting LDL cholesterol for Lp(a) cholesterol. The proportion of FH patients defined by DLCN (probable/definite) and SB (possible/definite) criteria decreased significantly in patients with increased Lp(a) (>0.5 g/L; n = 330) after Lp(a) cholesterol adjustment (P < 0.01). The overall reclassification rate was significantly higher in patients with Lp(a) concentration >1.0 g/L (P < 0.001). The AUROC curve for LDL cholesterol concentration ≥191 mg/dL (≥5.0 mmol/L), DLCN criteria, and SB criteria in predicting an FH mutation increased significantly after adjustment (P < 0.001). There was no significant difference in AUROC curve before and after Lp(a) cholesterol adjustment at an LDL cholesterol concentration ≥251 mg/dL (≥6.5 mmol/L). Adjusting LDL cholesterol concentration for Lp(a) cholesterol improves the diagnostic accuracy of DLCN and SB criteria, especially with Lp(a) >1.0 g/L and LDL cholesterol <251 mg/dL (<6.5 mmol/L). Lp(a) should be measured in all patients suspected of having FH.

A Novel Modified System of Simplified Chinese Criteria for Familial Hypercholesterolemia (SCCFH).

The most significant clinical implication of familial hypercholesterolemia (FH) is early-onset coronary artery disease (CAD), highlighting the importanceof a definitive diagnosis being available. Unfortunately, the existing algorithms are complex and it is often difficult to obtain information on the patient's family history. Hence, we aimed to establish a novel system of Simplified Chinese Criteria for FH (SCCFH). We recruited 12,921 participants undergoing routine blood collection from November 2011 to June 2018. Clinical characteristics, laboratory examination, and genetic testing were obtained. FH was diagnosed based on the Simon Broome (SB) criteria, Dutch Lipid Clinic Network (DLCN) criteria, and SCCFH. The sensitivity, specificity, and agreement of SCCFH to these existing criteria were investigated. Of 12,921 participants reviewed, the prevalence of definite FH was 223 (1.73%), 202 (1.56%), and 205 (1.59%) based on the DLCN, SB, and SCCFH approaches, respectively. Compared with the DLCN and SB criteria, the SCCFH showed high sensitivity (91.9% and 100%), high specificity (100% and 99.9%), and good agreement (κ = 0.958 and 0.993). Similar results were found in several relevant clinical subgroups. The SCCFH system is comparable to the existing criteria with high levels of sensitivity and specificity, and is easier to use clinically. Further larger prospective studies are needed to evaluate the feasibility and reliability of this system.

THE HIGH PREVALENCE OF FAMILIAL HYPERCHOLESTEROLEMIA IN A POPULATION OF ASCVD PATIENTS WITH LDL-C ABOVE TARGET: AN ANALYSIS FROM THE REACT REGISTRY

Heterozygous familial hypercholesterolemia (FH) prevalence is 1/250 in the general population and 1/125 in ASCVD patients, yet only a minority of patients are formally diagnosed. FH rises significantly with baseline LDL-cholesterol (LDL-C) levels above 5 mmol/L. Early identification and aggressive lipid-lowering therapy is thought to have substantial benefit on prevention of cardiovascular morbidity and mortality. We used a validated imputation for baseline (untreated) LDL-C levels and determined the prevalence of FH in this group, based on accepted international criteria and a new Canadian definition for FH. We intended to prospectively enroll 1800 patients with either established atherosclerotic CV disease (ASCVD) or FH (diagnosed based on traditional criteria), with LDL-C level >3.0mmol/L despite maximally tolerated statin therapy, as part of a national registry (REACT program-Relating Evidence to Achieve Cholesterol Targets). The sponsor terminated funding prematurely, resulting in 195 enrolled patients. We used a validated imputation for baseline (untreated) LDL-C levels, along with other clinical criteria to determine prevalence of FH, using accepted international criteria and a new Canadian definition for FH. Patients were categorized by enrolling physicians as either ASCVD or FH. There were 109 men and 86 women (76% Caucasian), mean age was 63±12 years. Diabetes (29.7%), hypertension (62.1%), smoking (37.9%) and family history of premature ASCVD (59.5%) were common. Six patients (3%) were diagnosed by enrolling physicians as having FH, the remaining as ASCVD. On-treatment LDL-C was 4.26±0.94mmol/L (mean±SD). Based on the dose and type of statin, +/- ezetimibe, imputed baseline or untreated LDL-C was 7.06±2.94mmol/L. A computerized algorithm was used to determine a diagnosis of FH incorporating additional clinical criteria. Using a cut-point of LDL-C >5.0mmol/L, 140/195(72%) of patients had severe hypercholesterolemia, the threshold for considering a diagnosis of FH in adults. Using the Simon-Broome criteria, 47/140(34%) had definite or 24/140(17%) probable FH, and using the Dutch Lipid Clinic Network 48/140(34%) had definite, 5/140(4%) probable or 80/140(57%) possible FH. Results mirror the new Canadian FH definition with 48/140(34%) definite or 13/140(9%) probable FH. This REACT analysis reveals a substantial proportion of ASCVD patients whose LDL-C levels remain above target in fact have probable or definite FH. Appropriate diagnosis of FH in these patients not only guides aggressive therapy, but has important implications for cascade screening and prevention in first degree relatives. Use of an imputed LDL-C in statin treated patients, and simplified tools for FH diagnosis should enable clinicians to more easily identify FH patients in their practices.

Cost-utility analysis of searching electronic health records and cascade testing to identify and diagnose familial hypercholesterolaemia in England and Wales

Background and aimsThe cost effectiveness of cascade testing for familial hypercholesterolaemia (FH) is well recognised. Less clear is the cost effectiveness of FH screening when it includes case identification strategies that incorporate routinely available data from primary and secondary care electronic health records. MethodsNine strategies were compared, all using cascade testing in combination with different index case approaches (primary care identification, secondary care identification, and clinical assessment using the Simon Broome (SB) or Dutch Lipid Clinic Network (DLCN) criteria). A decision analytic model was informed by three systematic literature reviews and expert advice provided by a NICE Guideline Committee. ResultsThe model found that the addition of primary care case identification by database search for patients with recorded total cholesterol >9.3 mmol/L was more cost effective than cascade testing alone. The incremental cost-effectiveness ratio (ICER) of clinical assessment using the DLCN criteria was £3254 per quality-adjusted life year (QALY) compared with case-finding with no genetic testing. The ICER of clinical assessment using the SB criteria was £13,365 per QALY (compared with primary care identification using the DLCN criteria), indicating that the SB criteria was preferred because it achieved additional health benefits at an acceptable cost. Secondary care identification, with either the SB or DLCN criteria, was not cost effective, alone (dominated and dominated respectively) or combined with primary care identification (£63, 514 per QALY, and £82,388 per QALY respectively). ConclusionsSearching primary care databases for people at high risk of FH followed by cascade testing is likely to be cost-effective.

Improving identification and management of familial hypercholesterolaemia in primary care: Pre- and post-intervention study

Background and aimsFamilial hypercholesterolaemia (FH) is a major cause of premature heart disease but remains unrecognised in most patients. This study investigated if a systematic primary care-based approach to identify and manage possible FH improves recommended best clinical practice. MethodsPre- and post-intervention study in six UK general practices (population 45,033), which invited patients with total cholesterol >7.5 mmol/L to be assessed for possible FH. Compliance with national guideline recommendations to identify and manage possible FH (repeat cholesterol; assess family history of heart disease; identify secondary causes and clinical features; reduce total & LDL-cholesterol; statin prescribing; lifestyle advice) was assessed by calculating the absolute difference in measures of care pre- and six months post-intervention. ResultsThe intervention improved best clinical practice in 118 patients consenting to assessment (of 831 eligible patients): repeat cholesterol test (+75.4%, 95% CI 66.9–82.3); family history of heart disease assessed (+35.6%, 95% CI 27.0–44.2); diagnosis of secondary causes (+7.7%, 95% CI 4.1–13.9), examining clinical features (+6.0%, 95% CI 2.9–11.7). For 32 patients diagnosed with possible FH using Simon-Broome criteria, statin prescription significantly improved (18.8%, 95% CI 8.9–35.3), with non-significant mean reductions in cholesterol post-intervention (total: −0.16 mmol/L, 95% CI -0.78-0.46; LDL: −0.12 mmol/L, 95% CI -0.81-0.57). ConclusionsWithin six months, this simple primary care intervention improved both identification and management of patients with possible FH, in line with national evidence-based guidelines. Replicating and sustaining this approach across the country could lead to substantial improvement in health outcomes for these individuals with very high cardiovascular risk.

Genetically Confirmed Familial Hypercholesterolemia in Patients With Acute Coronary Syndrome

BackgroundGenetic screening programs in unselected individuals with increased levels of low-density lipoprotein cholesterol (LDL-C) have shown modest results in identifying individuals with familial hypercholesterolemia (FH). ObjectivesThis study assessed the prevalence of genetically confirmed FH in patients with acute coronary syndrome (ACS) and compared the diagnostic performance of FH clinical criteria versus FH genetic testing. MethodsGenetic study of 7 genes (LDLR, APOB, PCSK9, APOE, STAP1, LDLRAP1, and LIPA) associated with FH and 12 common alleles associated with polygenic hypercholesterolemia was performed in 103 patients with ACS, age ≤65 years, and LDL-C levels ≥160 mg/dl. Dutch Lipid Clinic (DLC) and Simon Broome (SB) FH clinical criteria were also applied. ResultsThe prevalence of genetically confirmed FH was 8.7% (95% confidence interval [CI]: 4.3% to 16.4%; n = 9); 29% (95% CI: 18.5% to 42.1%; n = 18) of patients without FH variants had a score highly suggestive of polygenic hypercholesterolemia. The prevalence of probable to definite FH according to DLC criteria was 27.2% (95% CI: 19.1% to 37.0%; n = 28), whereas SB criteria identified 27.2% of patients (95% CI: 19.1% to 37.0%; n = 28) with possible to definite FH. DLC and SB algorithms failed to diagnose 4 (44%) and 3 (33%) patients with genetically confirmed FH, respectively. Cascade genetic testing in first-degree relatives identified 6 additional individuals with FH. ConclusionsThe prevalence of genetically confirmed FH in patients with ACS age ≤65 years and with LDL-C levels ≥160 mg/dl is high (approximately 9%). FH clinical algorithms do not accurately classify patients with FH. Genetic testing should be advocated in young patients with ACS and high LDL-C levels to allow prompt identification of patients with FH and relatives at risk.

Feasibility of improving identification of familial hypercholesterolaemia in general practice: intervention development study

ObjectivesTo assess the feasibility of improving identification of familial hypercholesterolaemia (FH) in primary care, and of collecting outcome measures to inform a future trial.DesignFeasibility intervention study.Setting6 general practices (GPs) in...

Premature coronary heart disease and autosomal dominant hypercholesterolemia: Increased risk in women with LDLR mutations

BackgroundFor patients with autosomal dominant hypercholesterolemia (ADH), it remains unclear whether differences exist in the risk of premature coronary heart disease (CHD) between patients with confirmed mutations in low-density lipoprotein receptor (LDLR) vs those without detectable mutations. ObjectiveThis study sought to assess the risk of premature CHD in ADH patients with mutations in LDLR (referred to as familial hypercholesterolemia [FH]) vs those without detectable mutations (unexplained ADH), stratified by sex. MethodsComparative study of premature CHD in a multiethnic cohort of 111 men and 165 women meeting adult Simon–Broome criteria for ADH. ResultsWomen with FH (n = 51) had an increased risk of premature CHD compared with unexplained ADH women (n = 111; hazard ratio [HR], 2.74; 95% confidence interval, 1.40–5.34; P = .003) even after adjustment for lipid levels and traditional CHD risk factors (HR, 2.53 [1.10–5.83]; P = .005). Men with FH (n = 42), in contrast, had a similar risk of premature CHD when compared with unexplained ADH men (n = 66; unadjusted: HR, 1.48 [0.84–2.63]; P = .18; adjusted: HR, 1.04 [0.46–2.37]; P = .72). To address whether mutation status provides additional information beyond LDL-cholesterol level, we analyzed premature CHD risk for FH vs unexplained ADH at various percentiles of LDL-cholesterol: the risk ratios were significant for women at 25th percentile (HR, 4.90 [1.69–14.19]) and 50th percentile (HR, 3.44 [1.42–8.32]) but not at 75th percentile (HR, 1.99 [0.95–4.17]), and were not significant for men at any percentile. ConclusionsOur findings suggest that genetic confirmation of ADH may be important to identify patient's risk of CHD, especially for female LDLR mutation carriers.

Familial hypercholesterolemia in China: Prevalence and evidence of underdetection and undertreatment in a community population

Familial hypercholesterolemia (FH) is the most common and serious monogenic disorder of lipid metabolism that causes premature coronary and heart disease [ [1] Watts G.F. Gidding S. Wierzbicki A.S. et al. Integrated guidance on the care of familial hypercholesterolaemia from the International FH Foundation. Int J Cardiol. 2014; 171: 309-325 Abstract Full Text Full Text PDF PubMed Scopus (276) Google Scholar ]. FH is often undetected and undertreated [ [1] Watts G.F. Gidding S. Wierzbicki A.S. et al. Integrated guidance on the care of familial hypercholesterolaemia from the International FH Foundation. Int J Cardiol. 2014; 171: 309-325 Abstract Full Text Full Text PDF PubMed Scopus (276) Google Scholar ]. The prevalence of FH is at least one in 500 in the general population, depending on diagnostic criteria [ [2] Benn M. Watts G.F. Tybjaerg-Hansen A. Nordestgaard B.G. Familial hypercholesterolemia in the Danish general population: prevalence, coronary artery disease, and cholesterol-lowering medication. J Clin Endocrinol Metab. 2012; 97: 3956-3964 Crossref PubMed Scopus (468) Google Scholar ]. Currently there is no consensus on the diagnosis of FH although the Dutch Lipid Clinic Network (DLCN) criteria have been widely used [ [1] Watts G.F. Gidding S. Wierzbicki A.S. et al. Integrated guidance on the care of familial hypercholesterolaemia from the International FH Foundation. Int J Cardiol. 2014; 171: 309-325 Abstract Full Text Full Text PDF PubMed Scopus (276) Google Scholar ]. In Asia, diagnostic criteria has been proposed by Harada-Shiba et al. [ [3] Harada-Shiba M. Arai H. Oikawa S. et al. Guidelines for the management of familial hypercholesterolemia. J Atheroscler Thromb. 2012; 19: 1043-1060 Crossref PubMed Scopus (144) Google Scholar ], but as with the Simon-Broome criteria from the UK [ [4] Scientific Steering Committee Simon Broome Register Group Risk of fatal coronary heart disease in familial hypercholesterolaemia. Scientific Steering Committee on behalf of the Simon Broome Register Group. BMJ. 1991; 303: 893-896 Crossref PubMed Google Scholar ], may have low sensitivity for detecting FH, since it does not use a numerical score and relies on the detection of tendon xanthomata, an infrequent sign in young subjects.

Familial hypercholesterolaemia (FH) in Wales is genetically heterogeneous

Familial hypercholesterolaemia (FH) in Wales is genetically heterogeneous

Analysis of the frequency and spectrum of mutations recognised to cause familial hypercholesterolaemia in routine clinical practice in a UK specialist hospital lipid clinic

AimTo determine the frequency and spectrum of mutations causing Familial Hypercholesterolaemia (FH) in patients attending a single UK specialist hospital lipid clinic in Oxford and to identify characteristics contributing to a high mutation detection rate. Methods289 patients (272 probands) were screened sequentially over a 2-year period for mutations in LDLR, APOB and PCSK9 using standard molecular genetic techniques. The Simon Broome (SB) clinical diagnostic criteria were used to classify patients and a separate cohort of 409 FH patients was used for replication. ResultsAn FH-causing mutation was found in 101 unrelated patients (LDLR = 54 different mutations, APOB p.(Arg3527Gln) = 10, PCSK9 p.(Asp374Tyr) = 0). In the 60 SB Definite FH patients the mutation detection rate was 73% while in the 142 with Possible FH the rate was significantly lower (27%, p < 0.0001), but similar (14%, p = 0.06) to the 70 in whom there was insufficient data to make a clinical diagnosis. The mutation detection rate varied significantly (p = 9.83 × 10−5) by untreated total cholesterol (TC) levels (25% in those <8.1 mmol/l and 74% in those >10.0 mmol/l), and by triglyceride levels (20% in those >2.16 mmol/l and 60% in those <1.0 mmol/l (p = 0.0005)), with both effects confirmed in the replication sample (p for trend = 0.0001 and p = 1.8 × 10−6 respectively). There was no difference in the specificity or sensitivity of the SB criteria versus the Dutch Lipid Clinic Network score in identifying mutation carriers (AROC respectively 0.73 and 0.72, p = 0.68). ConclusionsIn this genetically heterogeneous cohort of FH patients the mutation detection rate was significantly dependent on pre-treatment TC and triglyceride levels.

Low Prevalence of Mutations in Known Loci for Autosomal Dominant Hypercholesterolemia in a Multiethnic Patient Cohort

BACKGROUND- Autosomal dominant hypercholesterolemia (ADH), characterized by elevated plasma levels of low-density lipoprotein (LDL)-cholesterol, is caused by variants in at least 3 different genes: LDL receptor (LDLR), apolipoprotein B-100, and proprotein convertase subtilisin-like kexin type 9. There is paucity of data about the molecular basis of ADH among ethnic groups other than those of European or Japanese descent. Here, we examined the molecular basis of ADH in a multiethnic patient cohort from lipid clinics in a large, urban US city. METHODS AND RESULTS- A total of 38 men and 53 women, aged 22 to 76 years, met modified Simon-Broome criteria for ADH and were screened for mutations in the exons and consensus splice sites of LDLR, and in selected exons of apolipoprotein B-100 and proprotein convertase subtilisin-like kexin type 9. Deletions and duplications of LDLR exons were detected with multiplex ligation-dependent probe amplification. Heterozygous variants in LDLR were identified in 30 patients and in apolipoprotein B-100 in 1 patient. The remaining 60 patients (65%) had unexplained ADH. A higher proportion of blacks (77%) than either non-Hispanic whites (57%) or Hispanics (53%) had unexplained ADH. Compared with patients with LDLR variants, those with unexplained ADH had lower levels of LDL-cholesterol (292 ± 47 mg/dL versus 239 ± 42 mg/dL, respectively; P<0.0001) and higher levels of high-density lipoprotein cholesterol (45 ± 12 mg/dL versus 54 ± 13 mg/dL, respectively; P=0.003). Our findings suggest that additional loci may contribute to ADH, especially in understudied populations such as blacks.