Potential Familial Hypercholesterolemia Research Articles

The effectiveness and barrier of reverse cascade screening for paediatric familial hypercholesterolaemia

Abstract Background Familial Hypercholesterolaemia (FH) is an autosomal dominant genetic disorder that is prevalent in one out of every 300 individuals in the general population. Recognized as an actionable condition, early diagnosis of FH in children is crucial to prevent the onset of atherosclerosis, and equally important is the identification of parents before the development of coronary artery disease events. Therefore, the significance of universal FH screening during childhood combined with reverse cascade screening has been increasingly acknowledged. To achieve these objectives, in our region, universal lipid screening is conducted in elementary schools for children aged 9 or 10 years, annually screening approximately 8,000 individuals, with those identified being referred through a three-step process to four major healthcare facilities within the prefecture. However, the effectiveness of reverse-cascade screening remains unclear. Purpose Our study aimed to assess the effectiveness of and identify barriers to implementing reverse cascade screening in conjunction with universal lipid screening. Methods We conducted a single-center, retrospective observational study from January 2018 to July 2023 and evaluated the utility of reverse cascade screening for children genetically diagnosed with FH following universal screening. This study analysed prevalent barriers and identified families with suspected FH through reverse cascade screening, counting those with Potential FH among second-degree relatives. Beyond successful identification, we categorized the frequently encountered barriers into five distinct categories: bereavement, prior cardiovascular events, dyslipidaemia with unspecified LDL-C levels, incomplete family history information, and inadequate disease awareness of FH. Reverse FH diagnosis adhered to current guidelines. Results and Discussion Of 151 paediatric patients referred to our facility, 67 were genotypically confirmed to have FH. Excluding 8 cases of divorce and 4 cases of tracking challenges, 55 patients were finally analysed. 62 patients were diagnosed with reverse FH, and appropriate treatment was initiated. Notably, 158 cases of Potential FH were identified. (25 first-degree and 133 second-degree relatives). While a higher number of reverse FH diagnoses were observed in first-degree relatives (55 cases), the diagnostic yield was lower among second-degree relatives (seven cases). Common barriers for second-degree relatives included dyslipidaemia with unspecified LDL-C levels (42 cases) and incomplete family history information (66 cases). Conclusion Integrating universal screening with reverse cascade screening facilitates the identification of new FH cases. A comprehensive strategy for diagnosing reverse FH is paramount, raising disease awareness, genetic testing, the development of a family-based care plan, and enhancing access to information and communication technologies.

Prevalence of genetically diagnosed familial hypercholesterolemia in Vietnamese patients with premature acute myocardial infarction.

Familial hypercholesterolemia (FH) is a genetic disorder that results in elevated low-density lipoprotein cholesterol (LDL-C) levels, which manifest early in the first decades of life. It is a major cause of premature coronary artery disease worldwide, leading to significant public health challenges. The prevalence of genetically determined FH in patients with premature coronary artery disease remains underestimated, particularly in developing countries. This study aimed to assess the prevalence of genetically defined FH in Vietnamese patients with premature acute myocardial infarction (AMI) in the Vietnamese population. This cross-sectional study enrolled 218 consecutive patients diagnosed with premature AMI who underwent coronary angiography. The low-density lipoprotein receptor (LDLR), apolipoprotein B, and proprotein convertase subtilisin-kexin type 9 genes were analyzed by next-generation sequencing. FH was diagnosed according to Dutch Lipid Clinic Network criteria. Among the patients with premature AMI who underwent coronary angiography, the mean age was 46.9 ± 6.1 years, with a predominance of males (83.9%). The prevalence of potential FH diagnosed using Dutch Lipid Clinic Network criteria was 14.7% (definite FH, 6.0%; probable FH, 8.7%). Pathogenic or likely pathogenic variants in LDLR, apolipoprotein B, and proprotein convertase subtilisin-kexin type 9 were found in 9 of 218 patients (4.1%), all of which were causative mutations in LDLR. Patients with premature AMI and FH had significantly greater LDL-C levels (217.6 vs 125.7 mg/dL) and more severe coronary artery lesions, as assessed by the Gensini score (100.3 vs 60.5), than did those in the No FH group. The prevalence of genetically determined FH among Vietnamese patients with premature AMI is relatively high. Screening and diagnosis of hereditary conditions in patients with premature AMI are essential to improve early detection and management and reduce the burden of coronary artery disease in this population.

Improving the Detection of Potential Cases of Familial Hypercholesterolemia: Could Machine Learning Be Part of the Solution?

Familial hypercholesterolemia (FH), while highly prevalent, is a significantly underdiagnosed monogenic disorder. Improved detection could reduce the large number of cardiovascular events attributable to poor case finding. We aimed to assess whether machine learning algorithms outperform clinical diagnostic criteria (signs, history, and biomarkers) and the recommended screening criteria in the United Kingdom in identifying individuals with FH-causing variants, presenting a scalable screening criteria for general populations. Analysis included UK Biobank participants with whole exome sequencing, classifying them as having FH when (likely) pathogenic variants were detected in their LDLR, APOB, or PCSK9 genes. Data were stratified into 3 data sets for (1) feature importance analysis; (2) deriving state-of-the-art statistical and machine learning models; (3) evaluating models' predictive performance against clinical diagnostic and screening criteria: Dutch Lipid Clinic Network, Simon Broome, Make Early Diagnosis to Prevent Early Death, and Familial Case Ascertainment Tool. One thousand and three of 454 710 participants were classified as having FH. A Stacking Ensemble model yielded the best predictive performance (sensitivity, 74.93%; precision, 0.61%; accuracy, 72.80%, area under the receiver operating characteristic curve, 79.12%) and outperformed clinical diagnostic criteria and the recommended screening criteria in identifying FH variant carriers within the validation data set (figures for Familial Case Ascertainment Tool, the best baseline model, were 69.55%, 0.44%, 65.43%, and 71.12%, respectively). Our model decreased the number needed to screen compared with the Familial Case Ascertainment Tool (164 versus 227). Our machine learning-derived model provides a higher pretest probability of identifying individuals with a molecular diagnosis of FH compared with current approaches. This provides a promising, cost-effective scalable tool for implementation into electronic health records to prioritize potential FH cases for genetic confirmation.

Prevalence and management of familial hypercholesterolaemia in patients with chest pain admitted to hospital: a retrospective observational study

ObjectivesPatients with familial hypercholesterolaemia (FH) are genetically burdened by a lifelong elevation of the low-density lipoprotein cholesterol (LDL-C) level, putting them at a very high risk of premature ischaemic heart...

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.

Possible explanations for the common clinical familial hypercholesterolemia phenotypes in the Faroe Islands

The prevalence of clinical familial hypercholesterolemia (FH) is very high in the Faroe Islands, but the possible causes are unknown. We aimed to describe potential genetic causes of FH in the Faroe Islands and to investigate whether levels of lipoprotein(a) and measures of dietary habits were associated with clinical FH in the Faroe Islands. In this case-control study, we identified potential clinical FH cases aged 18-75 years registered within a nationwide clinical laboratory database in the Faroe Islands and invited them for diagnostic evaluation according to clinical FH scoring systems. Controls were identified in the background population. Lipoprotein(a) was measured in plasma, while the fatty acid composition was determined in adipose tissue. The habitual diet of the participants was assessed using a food frequency questionnaire. Genetic testing for FH and polygenic variants was performed in a selection of clinical FH cases. A total of 121 clinical FH cases and 123 age- and sex-matched controls were recruited. We found a very low frequency of monogenic FH (2.5%), but a high level of polygenic FH (63%) in those genetically tested (67%). High levels of plasma lipoprotein(a) were associated with high odds of clinical FH. Clinical FH cases had a lower intake of saturated fatty acids (SFAs) measured by a high fat-score and a lower content of SFAs in adipose tissue compared with controls. The high prevalence of FH in the Faroe Islands may be due to polygenic causes of hypercholesterolemia and to a lesser extent other genetic factors and elevated plasma lipoprotein(a) levels.

An evaluation of the effectiveness of a lipid clinic in identifying people with familial hypercholesterolaemia and reducing their risk of cardiovascular disease

Abstract Introduction The NHS Long Term Plan aims to ‘prevent up to 150,000 heart attacks, strokes and dementia cases over the next 10 years’.1 People with Familial Hypercholesterolaemia (FH) are considered to be at high-risk of heart attack, stroke and dementia but an estimated 90% remain undiagnosed.1 The Chesterfield and Dronfield Primary Care Network were commissioned to set-up a 12-month pharmacist-led clinic across 9 practices to identify, treat and refer FH patients. Patients with suspected FH benefit from referral to specialist services.2 Aim This study aimed to evaluate the number of FH patients identified and any unintended benefits of the Lipid Clinic. Methods Ethical approval was not required for this service evaluation. Informed consent was sought prior to data collection and the dataset was anonymised. Searches of practice patient records identified patients with a previously raised lipid level (total Cholesterol >7.5mmol/L and/or non-HDL-C > 5.9mmol/L)2 for review in the Lipid Clinic. Patients reviewed in the Lipid Clinic were initiated/optimised on lipid lowering medication as appropriate.2 Data were collected for patients invited for review in the Lipid Clinic between May-July 2022. Patients’ attendance as well as decline/non-response to the Clinic was recorded. The data collected included family history, QRISK score (where applicable), lipid lowering treatment the patient was taking (if any) and blood tests results (serum lipids, HBA1c and thyroid function tests). If bloods were deranged it was documented whether or not it was a new finding. The data was analysed by categorising patients into potential FH, primary/secondary prevention of cardiovascular disease and whether they needed referral to secondary care. Results Out of the 260 patients invited for review, 219 attended the clinic. Of these, 30 (13.7%) were provided with lifestyle advice as they did not meet the criteria for treatment. Twenty-three patients (10.5%) met the Simon-Broom criteria for possible FH. A further 3 patients identified were known to have FH but had not undergone genetic cascade testing. These 26 patients (11.8%) were referred to secondary care for genetic testing and specialist input. Newly raised HbA1c indicative of either diabetes or non-diabetic hyperglycaemia was incidentally found in 39 patients (17.8%). Lipid-lowering medication was initiated/titrated in 189 patients (86.3%). Discussion/Conclusion The significant proportion of patients requiring follow up in secondary care (11.8%) suggesting targeted searches are effective in identifying patients with possible FH. Identifying FH patients, testing and treating their family members appropriately reduces their risk of cardiovascular events.2 The Lipid Clinic has identifying that nearly a fifth of patients were previously undiagnosed with either diabetes or non-diabetic hyperglycaemia (17.8%) suggests that this is also an opportunity to identify and treat these patients earlier than they would otherwise have been identified. The results highlight the need for primary care staff education on the new AAC NHS Guidelines2 relating to managing lipid results. One limitation of the study is although the Lipid Clinic has received good informal feedback, formal feedback is yet to be collected from patients and stake holders. In addition, the clinic is still ongoing, and more data is being collected.

Genetic Spectrum of Familial Hypercholesterolaemia in the Malaysian Community: Identification of Pathogenic Gene Variants Using Targeted Next-Generation Sequencing

Familial hypercholesterolaemia (FH) is caused by mutations in lipid metabolism genes, predominantly in low-density lipoprotein receptor (LDLR), apolipoprotein B (APOB), proprotein convertase subtilisin/kexin-type 9 (PCSK9) and LDL receptor adaptor protein 1 (LDLRAP1). The prevalence of genetically confirmed FH and the detection rate of pathogenic variants (PV) amongst clinically diagnosed patients is not well established. Targeted next-generation sequencing of LDLR, APOB, PCSK9 and LDLRAP1 was performed on 372 clinically diagnosed Malaysian FH subjects. Out of 361 variants identified, 40 of them were PV (18 = LDLR, 15 = APOB, 5 = PCSK9 and 2 = LDLRAP1). The majority of the PV were LDLR and APOB, where the frequency of both PV were almost similar. About 39% of clinically diagnosed FH have PV in PCSK9 alone and two novel variants of PCSK9 were identified in this study, which have not been described in Malaysia and globally. The prevalence of genetically confirmed potential FH in the community was 1:427, with a detection rate of PV at 0.2% (12/5130). About one-fourth of clinically diagnosed FH in the Malaysian community can be genetically confirmed. The detection rate of genetic confirmation is similar between potential and possible FH groups, suggesting a need for genetic confirmation in index cases from both groups. Clinical and genetic confirmation of FH index cases in the community may enhance the early detection of affected family members through family cascade screening.

Subclinical atherosclerosis determined by coronary artery calcium deposition in patients with clinical familial hypercholesterolemia

Background and aimsLimited knowledge exists regarding the association between coronary artery calcium (CAC) deposition in patients with clinical familial hypercholesterolemia (FH) and FH subtypes such as polygenic causes. We studied CAC score in patients with clinical FH and subtypes including polygenic causes of FH compared to healthy controls. MethodsIn a case-control study, we identified potential clinical FH cases registered with an LDL-C >6.7 mmol/l within a nationwide clinical laboratory database on the Faroe Islands and invited them for diagnostic evaluation according to clinical FH scoring systems. Controls were identified in the background population. All subjects were aged 18–75 years and without a history of cardiovascular disease. FH mutation testing and genotypes of twelve LDL-C associated single nucleotide polymorphisms were determined using conventional methods in selected individuals. CAC scores were assessed by cardiac CT. Odds ratios obtained using multivariate logistic regression were used as measures of association. ResultsA total of 120 clinical FH patients and 117 age- and sex-matched controls were recruited. We found a very low frequency of monogenic FH (3%), but a high level of polygenic FH (60%) in those genetically tested (54%). There was a statistically significant association between the CAC score and a diagnosis of clinical FH with the highest observed odds ratio of 5.59 (95% CI 1.65; 18.94, p = 0.006) in those with a CAC score ≥300 compared to those with a CAC of zero. In supplemental analyses, there was a strong association between CAC scores and clinical FH of a polygenic cause. ConclusionWe found a statistically significant association between CAC levels and clinical FH with the highest observed risk estimates among clinical FH cases of a presumed polygenic cause.

Elevated Lipoprotein(a) Level Influences Familial Hypercholesterolemia Diagnosis.

Familial hypercholesterolemia (FH) and elevated lipoprotein(a) [Lp(a)] level are the most common inherited disorders of lipid metabolism. This study evaluated the impact of high Lp(a) level on accuracy Dutch Lipid Clinic Network (DLCN) criteria of heterozygous FH diagnosis. A group of 206 individuals not receiving lipid-lowering medication with low-density lipoprotein cholesterol (LDL-C) >4.9 mmol/L was chosen from the Russian FH Registry. LDL-C corrected for Lp(a)-cholesterol was calculated as LDL-C − 0.3 × Lp(a). DLCN criteria were applied before and after adjusting LDL-C concentration. Of the 206 patients with potential FH, a total of 34 subjects (17%) were reclassified to less severe FH diagnosis, 13 subjects of them (6%) were reclassified to “unlike” FH. In accordance with Receiver Operating Characteristic curve, Lp(a) level ≥40 mg/dL was associated with FH re-diagnosing with sensitivity of 63% and specificity of 78% (area under curve = 0.7, 95% CI 0.7–0.8, p < 0.001). The reclassification was mainly observed in FH patients with Lp(a) level above 40 mg/dL, i.e., 33 (51%) with reclassified DLCN criteria points and 22 (34%) with reclassified diagnosis, compared with 21 (15%) and 15 (11%), respectively, in patients with Lp(a) level less than 40 mg/dL. Thus, LDL-C corrected for Lp(a)-cholesterol should be considered in all FH patients with Lp(a) level above 40 mg/dL for recalculating points in accordance with DLCN criteria.

Lipoprotein(a) and autoantibodies against lipoprotein(a) and СHD in middle-age patients with potential FH

Background and Aims: Familial hypercholesterolemia (FH) and elevated Lp(a) level [hyperLp(a)] as hereditary disorders of lipid metabolism are the main cause of the development of atherosclerosis and CHD. Autoimmune reactions can be involved in atherogenesis. The aim of this study was to investigate the contribution of hyperLp(a) and autoantibodies (autoAbs) against Lp(a) in the development of CHD in patients with potential FH under the age of 60 years.

Familial Hypercholesterolaemia in the Malaysian Community: Prevalence, Under-Detection and Under-Treatment.

Aim: Familial hypercholesterolaemia (FH) is the most common autosomal dominant lipid disorder, leading to severe hypercholesterolaemia. Early detection and treatment with lipid-lowering medications may reduce the risk of premature coronary artery disease in FH patients. However, there is scarcity of data on FH prevalence, detection rate, treatment and control with lipid-lowering therapy in the Malaysian community. Methods: Community participants ( n =5130) were recruited from all states in Malaysia. Blood samples were collected for lipid profiles and glucose analyses. Personal and family medical histories were collected by means of assisted questionnaire. Physical examination for tendon xanthomata and premature corneal arcus were conducted on-site. FH were clinically screened using Dutch Lipid Clinic Network Criteria. Results: Out of 5130 recruited community participants, 55 patients were clinically categorised as potential (Definite and Probable) FH, making the prevalence FH among the community as 1:100. Based on current total population of Malaysia (32 million), the estimated number of FH patients in Malaysia is 320,000, while the detection rates are estimated as 0.5%. Lipid-lowering medications were prescribed to 54.5% and 30.5% of potential and possible FH patients, respectively, but none of them achieved the therapeutic LDL-c target. Conclusion: Clinically diagnosed FH prevalence in Malaysian population is much higher than most of the populations in the world. At community level, FH patients are clinically under-detected, with majority of them not achieving target LDL-c level for high-risk patients. Therefore, public health measures are warranted for early detection and treatment, to enhance opportunities for premature CAD prevention.

Screening for potential familial hypercholesterolaemia in general practice: an observational study on prevalence and management.

BackgroundFamilial hypercholesterolaemia (FH) is a common genetic disorder causing premature cardiovascular disease (CVD). The estimated prevalence of probable or definite FH is 1:200–250 individuals, according to the Dutch Lipid Clinic Network (DLCN) criteria for FH. In Denmark approximately 12% of cases are identified.AimTo provide knowledge of the prevalence and management of FH in general practice.Design & settingA collaboration between six general practice clinics and the department of cardiology at Bispebjerg hospital in Denmark.MethodA total of 9652 patient records were screened for hypercholesterolaemia. All patients with a low-density lipoprotein cholesterol (LDL-C) ≥5.0 mmol/l were included in the study population and their records were investigated in order to perform a diagnostic score according to the DLCN criteria.ResultsIt was found that 2382 individuals had a lipid measurement available, and 236 of those had an LDL-C ≥5.0 mmol/l. In total, 34 individuals were found to have probable or definite FH (DLCN score ≥5). Only three individuals had been diagnosed and treated with lipid-lowering therapy. Of 236 individuals with high LDL-C, only 25 individuals met their treatment target. By excluding patients with signs of secondary hypercholesterolaemia, a subgroup of 115 individuals with potential primary hypercholesterolaemia was established. Among those, 21 individuals were found to have probable or definite FH (1:114 individuals).ConclusionThe study shows that there is a massive lack of recognition of FH in general practice. Despite a measured high LDL-C, the diagnosis is rarely made and only a few patients are treated accordingly. Of the patients undergoing treatment, only a few reached their treatment target.

Prevalence of Familial Hypercholesterolaemia in Acute Coronary Syndrome Patients in a Large Regional Coronary Care Unit

Familial hypercholesterolaemia (FH) is an under recognised cause of coronary artery disease, despite the proven reductions in risk with early detection and treatment. Data from 180 consecutive patients presenting to a large regional hospital with acute coronary syndrome were collected. Potential FH was assessed using the Dutch Lipid Clinic Network Criteria (DLCNC), and if patients were on statins, pre-treatment cholesterol was estimated according to a validated algorithm. Ninety per cent (90%) of patients presented with non-ST elevation myocardial infarction (NSTEMI) or ST elevation myocardial infarction (STEMI). A total of 11 patients (6%) were classified as having phenotypic FH. The phenotypic FH cohort was younger (mean age 53.1 vs 62.0, p=0.011); and more likely to have documented ischaemic heart disease (63.6% vs 20.7%, p=0.001). Familial hypercholesterolaemia patients had a higher rate of ezetimibe use (18.2% vs 2.4%, p=0.005), but fibrate use was not significantly different. Phenotypic FH patients also had higher levels of total cholesterol, corrected LDL and triglycerides, but no statistically significant difference in HDL levels compared with non-FH counterparts. The prevalence of FH is relatively high among patients presenting with acute coronary syndromes. This has now been established in a regional Australian population, with similar prevalence to large European registries. This highlights the need for improved access to specialised services in regional and rural areas to reduce adverse cardiovascular (CV) outcomes.

A reassessment of the Japanese clinical diagnostic criteria of familial hypercholesterolemia in a hospital-based cohort using comprehensive genetic analysis

BackgroundClinical diagnostic criteria of familial hypercholesterolemia (FH) in Japan include LDL cholesterol ​≥ ​180 ​mg/dL, Achilles tendon thickness ​≥ ​9.0 ​mm, and family history. However, few data exist regarding its validation. Design and MethodsA series of 680 participants, with a mean LDL cholesterol of 175 ​mg/dL were enrolled at Kanazawa University Hospital between 2006 and 2018. All had full assessments of, LDL cholesterol, Achilles tendon X-rays, family history records, and genetic analysis of FH-associated genes (LDLR, APOB, and PCSK9). The area under the curve (AUC) of receiver operating characteristic (ROC) curve analysis predicting the presence of FH mutations by each clinical marker were assessed. ResultsThe optimal cutoff values predicting the presence of an FH-associated mutation were 181 ​mg/dL for LDL cholesterol and ≥7.0 ​mm for Achilles tendon thickness. AUCs predicting FH mutations were 0.827 for Achilles tendon thickness ≥9.0 ​mm, 0.889 for LDL cholesterol ≥180 ​mg/dL, and 0.906 for family history. If Achilles tendon thickness ≥7.0 ​mm was used as a clinical criterion, then 41 participants (6%) were newly diagnosed with FH and 86 (12%) were newly misclassified as FH. ConclusionsCurrent clinical diagnostic criteria of FH were validated in this cohort. We recommend considering a tentative diagnosis of “potential FH” if the Achilles tendon thickness is ​≥ ​7.0 ​mm and <9.0 ​mm rather than dismissing a diagnosis of FH.

Prevalence Of familial hypercholeSTerolaemia (FH) in Italian Patients with coronary artERy disease: The POSTER study

Background and aimsFamilial hypercholesterolaemia (FH) is a powerful risk factor for cardiovascular (CV) events. High levels of low-density lipoprotein cholesterol (LDL-C) since birth are linked to the early onset of atherosclerotic disease. A genetic mutation determining FH is present in about one subject out of 250; FH should be more represented among subjects with a documented diagnosis of coronary artery disease (CAD). The POSTER Study evaluated the prevalence of FH in Italian patients with a recent CAD event. MethodsEighty-two cardiology centres enrolled patients with a documented CAD event; CV risk profile, drug therapy and biochemical parameters were collected. Dutch Lipid Clinic Network (DLCN) criteria were used to define patients with a potential FH diagnosis (score ≥6); these patients underwent molecular testing for genetic diagnosis of FH. ResultsOverall, 5415 patients were enrolled and the main index events were myocardial infarction with ST-elevation, non ST-elevation acute coronary syndrome (ACS), or a recent coronary revascularization (34.8%, 37.2%, and 28% respectively). Mean age was 66 ± 11 years, men were 78%; about 40% were already treated with statins, proportion that increased after the acute event (96.5%). Based on the DLCN score, the prevalence of potential FH was 5.1%, 0.9% of them had a diagnosis of definite FH (score >8). These patients were younger than patients with a score <6 (56 ± 10 vs 66 ± 11, p < 0.001), and LDL-C levels were in most of them (~87%) >190 mg/dL. FH was genetically confirmed in 42 subjects (15.9%); genetic diagnosis was defined as not conclusive for FH in 63 patients (23.9%). Finally, in 159 subjects (60.2%) no pathogenic mutations in the tested genes were identified, defining them as negative for monogenic familial hypercholesterolemia. ConclusionsResults underscore a relatively high prevalence of potential FH in patients with a recent CAD event. Therefore, an early identification of these subjects may help improve the management of their high CV risk and, by cascade screening, identify possible FH relatives.

Screening and treatment of Familial Hypercholesterolemia in a French sample of ambulatory care: A retrospective longitudinal cohort study

Familial hypercholesterolemia (FH) is underdiagnosed, physicians from an electronic medical record (EMRs) were alerted to LDL-C levels > 190 mg/dL and invited to complete the Dutch Lipid Clinic Network score (DLCN). Describe characteristics, comorbidities and clinical management of patients diagnosed with definite or probable FH in an ambulatory care setting. All patients with a DLCN score of definite/probable FH (score higher or equal than 6) between January 2016 and September 2018 were identified in the THIN® database (The Health Improvement Network; an anonymized EMR powered by GERSDATA, a Cegedim Health Data Division). These fully anonymized data were collected by 2000 General Practitioners, 130 cardiologists and 40 endocrinologists, receiving 5.5 million patients regularly in their office. From 999 anonymous patients with a DLCN score, 98 (10%) FH patients were identified (38 [39%] definite FH, 60 [61%] probable FH), 9 (9%) of whom already had genetic testing. Mean (SD) age was 57.4 (14.3) years; 56 (57%) patients were female, half (51/98 [52%]) were diagnosed with pure hypercholesterolemia (ICD-10 code: E78.0) and 9 (9%) had a history of CV event. Sixty patients (61.2%) had LDL-C between 190 to 250 mg/dL and 16 (16.3%) had LDL-C higher than 250 mg/dL. At the time of DLCN assessment, one third (30/98 [31%]) of patients were not receiving any LLT, one third (34/98 [35%]) were receiving statins alone, 19% [19/98) receiving LLT combination with statin, and 15 (15%) other LLTs. Moderate statin intensity was prescribed in 20% (20/98) of patients; high intensity statin, 17%, (17/98); low intensity, 10% (10/98). No improvement on LLT use (including use of high statin intensity) was observed over the 12-month follow-up. This is the first study in France that use EMR to screen possible FH patients. Our data highlight the need to screen, diagnosis and treat potential FH patients in ambulatory care settings.

Finding missed cases of familial hypercholesterolemia in health systems using machine learning

Familial hypercholesterolemia (FH) is an underdiagnosed dominant genetic condition affecting approximately 0.4% of the population and has up to a 20-fold increased risk of coronary artery disease if untreated. Simple screening strategies have false positive rates greater than 95%. As part of the FH Foundation′s FIND FH initiative, we developed a classifier to identify potential FH patients using electronic health record (EHR) data at Stanford Health Care. We trained a random forest classifier using data from known patients (n = 197) and matched non-cases (n = 6590). Our classifier obtained a positive predictive value (PPV) of 0.88 and sensitivity of 0.75 on a held-out test-set. We evaluated the accuracy of the classifier′s predictions by chart review of 100 patients at risk of FH not included in the original dataset. The classifier correctly flagged 84% of patients at the highest probability threshold, with decreasing performance as the threshold lowers. In external validation on 466 FH patients (236 with genetically proven FH) and 5000 matched non-cases from the Geisinger Healthcare System our FH classifier achieved a PPV of 0.85. Our EHR-derived FH classifier is effective in finding candidate patients for further FH screening. Such machine learning guided strategies can lead to effective identification of the highest risk patients for enhanced management strategies.

Current Status of Familial Hypercholesterolemia in China: A Need for Patient FH Registry Systems.

Background: Familial hypercholesterolemia (FH) greatly facilitates the development of cardiovascular disease (CVD). Without timely treatment, the incidence of coronary heart disease (CHD) in patients with FH is 3 to 4 times that in non-FH patients, and the onset of CVD would be advanced by approximately 10 years. There is ample evidence that the diagnosis and adequate treatment of FH are not properly considered for all ethnicities. The monogenic cause of FH includes apolipoprotein B (APOB), low-density lipoprotein receptor (LDLR), and proprotein convertase subtilisin/kexin 9 (PCSK9). There are approximately 2,765,420 to 6,913,550 cases of potential heterozygous FH (HeFH) and 2,205 to 4,609 cases of potential homozygous FH (HoFH) in China. Nevertheless, China lacks clinical diagnostic criteria specific to Chinese patients, such that most FH patients cannot be diagnosed until middle age or after their first cardiovascular event, thus precluding early treatment.Objective: This article explores the gene mutations, diagnosis and treatment of FH patients in China. Following the implementation of the two-child policy, there is a need to establish Chinese FH registry systems and genetic databases and to address the challenges in conducting cascade screening and long-term management.Conclusion: Advocating the establishment of FH registry systems and databases is an important rate-limiting step in improving long-term prognosis in FH patients, so that joint efforts of clinical experts and public communities are required. We recommend a process flow from case identification to entry into the registry system, and the widespread use of the system in clinical applications can provide the best treatment guidance for medical practice.

Genetic Testing and Risk Scores: Impact on Familial Hypercholesterolemia.

Familial Hypercholesterolemia (FH) is an inherited lipid disorder affecting 1 in 220 individuals resulting in highly elevated low-density lipoprotein levels and risk of premature coronary disease. Pathogenic variants causing FH typically involve the LDL receptor (LDLR), apolipoprotein B-100 (APOB), and proprotein convertase subtulisin/kexin type 9 genes (PCSK9) and if identified convey a risk of early onset coronary artery disease (ASCVD) of 3- to 10-fold vs. the general population depending on the severity of the mutation. Identification of monogenic FH within a family has implications for family-based testing (cascade screening), risk stratification, and potentially management, and it has now been recommended that such testing be offered to all potential FH patients. Recently, robust genome wide association studies (GWAS) have led to the recognition that the accumulation of common, small effect alleles affecting many LDL-c raising genes can result in a clinical phenotype largely indistinguishable from monogenic FH (i.e., a risk of early onset ASCVD of ~3-fold) in those at the extreme tail of the distribution for these alleles (i.e., the top 8% of the population for a polygenic risk score). The incorporation of these genetic risk scores into clinical practice for non-FH patients may improve risk stratification but is not yet widely performed due to a less robust evidence base for utility. Here, we review the current status of FH genetic testing, potential future applications as well as challenges and pitfalls.