Abstract
Background
Familial hypercholesterolemia (FH) is a common autosomal dominant disease associated with premature coronary heart disease (CHD). Studies tend to show that patients with FH associated with an identified mutation (mutation+ FH) are at higher risk than patients without an identified mutation (mutation– FH). We compared the clinical and biological profile and the risk of CHD in patients with mutation+ FH and mutation– FH.
Hypothesis
In addition to LDL‐C, a pathogenic mutation predicts premature CHD in FH.
Methods
We successively included all patients with suspected FH (LDL‐C > 190 mg/dL if age > 18 years; LDL‐C > 160 mg/dL if age < 18 years) and compared patients with a pathogenic mutation with those without an identified pathogenic mutation.
Results
We studied 179 patients with mutation+ FH and 147 with mutation– FH. The mean age was 44 (± 18) years. The lipid profile was more atherogenic in those with mutation+ FH, who had higher LDL‐C (254 ± 69 mg/dL vs 218 ± 35 mg/dL; P < 0.01) and lower HDL‐C (53 ± 14 mg/dL vs 58 ± 17 mg/dL; P < 0.01). Despite the more atherogenic nonlipid cardiovascular profile of patients with mutation– FH, the age of CHD onset was earlier in patients with mutation+ FH (48 vs 56 years; P = 0.026). After multiple adjustment, the presence of a positive mutation was significantly associated with premature CHD (OR: 3.0, 95% CI: 1.38‐6.55, P < 0.01).
Conclusions
Patients with mutation+ FH have a more atherogenic lipid profile and a 3‐fold higher risk of premature CHD, as well as earlier onset of CHD, than patients with mutation– FH.
Keywords: Dutch Lipid Clinic Network, Familial Hypercholesterolemia, Mutations, Premature Coronary Heart Disease
1. INTRODUCTION
Familial hypercholesterolemia (FH) is a common autosomal dominant disease associated with high cardiovascular (CV) risk.1, 2, 3, 4 The risk of developing premature coronary heart disease (CHD) is estimated at between 10× and 20× times higher than in the general population, with a frequency evaluated at 1 in 200.5, 6
The clinical and biological diagnosis of FH is based on the Dutch Lipid Clinic Network (DLCN) score.1 The presence of a causal mutation in the genes coding for the low‐density lipoprotein (LDL) receptor, for proprotein convertase subtilisin/kexin type 9 (PCSK9), or for apolipoprotein B (apoB) is scored 8 and identifies FH.
Between 10% and 40% of patients with a clinical and biological diagnosis of FH do not have an identified mutation.7 Thus, 2 entities are differentiated: mutation‐positive (mutation+) FH with an identified FH‐causing mutation, and mutation‐negative (mutation–) FH, with no identified mutation.8 Mutation– FH may be polygenic due to inheritance of a high number of common low‐density lipoprotein cholesterol (LDL‐C) raising alleles7 or environmental factors such as a high saturated fat intake, weight gain, or menopausal status.9
Finally, mutation+ FH patients appear to be at higher CV risk than mutation– patients.9, 10, 11, 12
A definite FH diagnosis1 results from the combination of clinical, biological, and genetic markers found in the DLCN score. Although several articles have analyzed each component of the DLCN score,3, 9, 11, 12, 13, 14, 15 only 1 published study16 recorded all these parameters in 181 patients; however, a formal multivariate analysis was not performed to predict premature CHD.
The objective of this study was to compare CV risk in patients with mutation+ FH and those with mutation– FH in a sample of 344 patients.
2. METHODS
2.1. Study population
We prospectively and consecutively included all patients with high LDL blood levels (LDL‐C > 190 mg/dL if age > 18 years or LDL‐C > 160 mg/dL if age < 18 years). A clinical examination, electrocardiogram, and full laboratory tests were carried out the same day. A DNA sample was taken after the patient had received full oral information and given written informed consent. All clinical and biological data were reported as previously described.17, 18 The present sample, composed of patients with a complete genetic determination, is a different sample of our 2 previous studies.17, 18 Authorization for the use of these data was obtained in accordance with French law (National Commission for Computing and Liberties, CNIL). The study protocol was consistent with the 1975 Declaration of Helsinki.
2.2. Standardized questionnaire
The standardized questionnaire detailed the main personal and family medical history, CV risk factors, current treatments, lifestyle, and results of the clinical examination. All items of the DLCN1 score were collected. Clinical examination included blood pressure (BP), clinical assessment of signs of lipid impregnation, height and weight measurement, and a 12‐lead electrocardiogram. Smoking was defined as active smoking or stopped for <3 years. Hypertension was defined as BP ≥140/90 mmHg at rest or current BP medication. Diabetes mellitus was defined as fasting glycemia ≥7 mmol/L or treatment with antidiabetic drugs.
2.3. Exploration of lipid abnormalities
Laboratory tests were performed after ≥10 hours of fasting. Serum cholesterol and triglyceride levels were analyzed using the enzymatic method (Boehringer; Mannheim, Germany). High‐density lipoprotein cholesterol (HDL‐C) was measured by precipitation with sodium phosphotungstate and magnesium chloride. LDL‐C was then calculated by the Friedewald formula when triglycerides were <400 mg/dL.19
If the patient was already treated with statins at the time of the consultation, and if a previous recent lipid assessment (<3 months) without statins was available, we used the lipid assessment without lipid‐lowering drugs. When no lipid measures were available prior to initiation of lipid‐lowering drugs, the corrected LDL‐C was estimated prior to the implementation of statin therapy as a function of statin potency, according to Stone et al.20 In patients for whom lipid results without statins were available, the corrected LDL‐C was the LDL‐C level without statins.
2.4. Genetic testing
Mutations in the LDLR gene, the gene encoding the LDL receptor, were sought by 2 methods of analysis of genomic DNA extracted from a venous blood sample. A point mutation or small‐size rearrangement was sought by polymerase chain reaction (PCR) followed by sequencing (forward and reverse) of the promoter, the 18 exons, and the flanking intronic regions (from –100 up to +50) of the LDLR gene. Electrophoretic migration was completed on the 3500xL Dx (CE IVD) genetic analyzer (Applied Biosystems, Paisley, Scotland) and compared with the reference sequence (NG_009060.1 covering the transcribed NM_000527.3) using Gensearch version 4.0.4 software (PhenoSystems, Wallonia, Belgium). The presence of a mutation was confirmed by a reaction of the targeted sequence (forward and reverse). Molecular diagnosis of a large rearrangement of the LDLR gene was performed by the multiple ligation‐dependent probe amplification (MLPA) technique (SALSA MLPA kit P062 LDLR; MRC‐Holland, Amsterdam, The Netherlands). Mutations of the PCSK9 gene were sought on genomic DNA by PCR followed by systematic sequencing (forward and reverse) of the 12 exons and flanking intronic regions (from –100 up to +50). Electrophoretic migration was completed on the 3500xL Dx (CE IVD) genetic analyzer (Applied Biosystems) and compared with the reference sequence (NG_0090611 covering the transcribed NM_174936.3) using Gensearch 4.0.4 software (PhenoSystems). The presence of a mutation was confirmed by a reaction of the targeted sequence (forward and reverse).
The Arg3527Gln mutation (or R3527Q initially named R3500Q) of the APOB gene encoding apoB was sought on genomic DNA by PCR restriction followed by electrophoretic migration.21
The causal or pathogenic nature of a mutation was determined in terms of its theoretical effect on the protein sequence, its frequency in the Leiden Open Variation Database (LOVD) public databases (specific locus), dbSNP (polymorphisms), and ExAC (exomes), as well as in the laboratory database, a literature search, and in‐silico simulations (Alamut 2.7.2).
When an already described and confirmed pathogenic mutation was identified, the patient was considered as presenting mutation+ FH. When no mutation was identified in the 3 genes, the patient was considered as presenting mutation– FH. When a mutation of uncertain pathogenicity was identified, the patient was excluded from analysis.
2.5. Statistical analysis
Statistical analysis was performed with STATA statistical software, release 11.2 (StataCorp LP, College Station, TX). We compared the continuous variables by using the Student t test or the Mann–Whitney U test. Qualitative variables were compared using the χ2 test or Fisher exact test. Multiple logistic regression was used for adjustment for the confounding factors. The original predictor variables were included in the multivariate model when their P value under univariate analysis was <0.10. For continuous variables, the hypothesis of log‐linearity was verified. When log‐linearity was not verified, the corresponding continuous variable was replaced by a qualitative variable. We also estimated the ability of the DLCN score and the LDL‐C level to classify a patient with FH in the mutation+ or mutation– category using ROC curves.
3. RESULTS
3.1. Study population
Of the 632 patients with dyslipidemia, 344 met the criteria for inclusion (LDL‐C > 190 mg/dL if age > 18 years or LDL‐C > 160 mg/dL if age < 18 years) and were genetically sampled (Figure 1). A mutation was identified in 197 patients: 180 proven pathogenic mutations and 17 mutations of unproven pathogenicity. One patient was homozygous (compound heterozygote) for the LDLR gene. No mutation was identified in the other 147 patients. After exclusion of the homozygous patient and the 17 patients with a mutation whose pathogenicity was not proven, we finally included 326 patients. One hundred seventy‐nine patients (54.9%) presented a mutation, whereas no mutation was identified in 147 (45.1%) patients. Of the 179 patients with a pathogenic mutation, 171 mutations were in the LDLR gene (95.5%) and 8 (4.5%) in the APOB gene. No PCSK9 gene mutations were found.
Figure 1.
Flowchart of patient inclusion. Abbreviations: APOB, gene encoding apolipoprotein B; LDL‐C, low‐density lipoprotein cholesterol; LDLR, gene encoding the LDL receptor; PCSK9, proprotein convertase subtilisin/kexin‐type 9
3.2. Description of the study population
Fifty‐two percent of patients had a family history of premature CHD and 87% had a family history of dyslipidemia. The prevalence of premature CHD was 13%. Average LDL‐C was 238 ± 59 mg/dL and 30% of patients were receiving statins. The LDL‐C corrected according to statin potency was 267 ± 72 mg/dL (Tables 1 and 2).
Table 1.
Clinical characteristics of the study population
| Parameters | All Patients, N = 326 | Mutation+ FH, n = 179 | Mutation– FH, n = 147 | P Value |
|---|---|---|---|---|
| Age, y | 44 ± 18 | 39 ± 17 | 51 ± 17 | <0.01 |
| Male sex | 147 (45) | 86 (48) | 61 (41) | 0.23 |
| First‐degree relative with premature CHD (<55 y men, <60 y women) | 170 (52) | 103 (57) | 67 (45) | 0.031 |
| First‐degree relative with LDL‐C > 95th percentile | 285 (87) | 164 (91) | 121 (83) | 0.022 |
| First‐degree relative with tendon xanthomas and/or corneal arcus | 1 (0.3) | 1 (0.6) | 0 (0) | 0.37 |
| Previous history of premature CHD (<55 y men, <60 y women) | 42 (13) | 32 (18) | 10 (7) | <0.01 |
| Age of CHD onset, y | 55 ± 12 | 48 ± 11 | 56 ± 12 | 0.026 |
| Previous history of premature vascular disease (<55 y men, <60 y women) | 32 (10) | 15 (8) | 17 (12) | 0.34 |
| Premature corneal arcus (<45 y) | 16 (5) | 14 (7.6) | 2 (1.4) | 0.012 |
| Xanthelasmas | 10 (3) | 6 (3) | 4 (3) | 0.99 |
| Tendon xanthomas | 13 (4) | 12 (6.3) | 1 (0.7) | <0.01 |
| Current smoker | 65 (20) | 31 (17) | 34 (23) | 0.15 |
| DM | 30 (9) | 9 (5) | 21 (14) | <0.01 |
| HTN | 62 (19) | 25 (14) | 37 (25) | 0.012 |
| BMI, kg/m2 | 24.3 ± 5.1 | 23.4 ± 5.1 | 25.5 ± 5.3 | <0.01 |
| SBP, mm Hg | 130 ± 18 | 127 ± 16 | 134 ± 19 | <0.01 |
| DBP, mm Hg | 78 ± 11 | 75 ± 10 | 81 ± 12 | <0.01 |
| DLCN score | 14.1 ± 6.5 | 18.9 ± 4.6 | 8.2 ± 2.7 | <0.01 |
| DLCN score (without genetic items) | 9.7 ± 4.0 | 11.0 ± 4.4 | 8.2 ± 2.7 | <0.01 |
| Statins | 99 (30) | 74 (41) | 25 (17) | <0.01 |
| Statin potency | <0.01 | |||
| High | 40 (12) | 36 (20) | 4 (3) | |
| Moderate | 48 (14) | 33 (18) | 15 (10) | |
| Low | 11 (3.3) | 5 (2.8) | 6 (4) | |
| Ezetimibe | 38 (12) | 30 (17) | 8 (5) | 0.099 |
| Cholestyramine | 5 (1.5) | 5 (2.8) | 0 (0) | 0.041 |
| Fibrates | 9 (2.8) | 6 (3.3) | 3 (2) | 0.47 |
Abbreviations: BMI, body mass index; CHD, coronary heart disease; DBP, diastolic blood pressure; DLCN, Dutch Lipid Clinic Network; DM, diabetes mellitus; FH, familial hypercholesterolemia; HTN, hypertension; LDL‐C, low‐density lipoprotein cholesterol; SBP, systolic blood pressure; SD standard deviation.
Data are presented as n (%) or mean ± SD.
Table 2.
Biological characteristics of the study population
| Parameters | All Patients, n = 326 | Mutation+ FH, n = 179 | Mutation– FH, n = 147 | P Value |
|---|---|---|---|---|
| sCr, mg/dL | 0.92 ± 0.21 | 0.89 ± 0.21 | 0.95 ± 0.20 | 0.048 |
| MDRD‐derived eGFR, mL/min/1.73 m2 | 101 ± 32 | 108 ± 37 | 94 ± 37 | <0.01 |
| Blood glucose, mmol/L | 5.1 ± 0.9 | 4.9 ± 0.7 | 5.3 ± 1.1 | <0.01 |
| TC, mg/dL | 315 ± 67 | 327 ± 79 | 302 ± 46 | <0.01 |
| LDL‐C, mg/dL | 238 ± 59 | 254 ± 69 | 218 ± 35 | <0.01 |
| Corrected LDL‐C, mg/dLa | 267 ± 72 | 296 ± 76 | 266 ± 72 | <0.01 |
| HDL‐C, mg/dL | 56 ± 16 | 53 ± 14 | 58 ± 17 | <0.01 |
| TG, mg/dL | 104 (75–161) | 90 (68–137) | 110 (82–174) | <0.01 |
| Lp(a), mg/dL | 20 (6–66) | 33 (3‐68) | 18 (3–63) | 0.19 |
Abbreviations: eGFR, estimated glomerular filtration rate; FH, familial hypercholesterolemia; HDL‐C, high‐density lipoprotein cholesterol; IQR, interquartile range; LDL‐C, low‐density lipoprotein cholesterol; Lp(a), lipoprotein(a); MDRD, Modification of Diet in Renal Disease; sCr, serum creatinine; SD, standard deviation; TC, total cholesterol; TG, triglycerides.
Data are presented as mean ± SD when distribution was normal or as median (IQR) when distribution was not normal.
Corrected LDL‐C: When naïve LDL‐C was not available because of lipid‐lowering medication, a corrected LDL‐C was estimated as a function of statin potency.
3.3. Comparison of mutation+ with mutation– FH patients
Mutation+ FH patients were younger than mutation– FH patients, with a mean age of 39 ± 17 vs 51 ± 17 years, respectively. They also presented fewer CV risk factors, as fewer patients had diabetes (5% vs 14%; P < 0.01) or high BP (14% vs 25%; P = 0.012). Fewer mutation‐positive patients were smokers (Tables 1 and 2 ).
Mutation+ FH patients were more likely than mutation– FH patients to have a family history of CHD (57% vs 45%, respectively; P = 0.031) or dyslipidemia (91% vs 83%; P = 0.022), or to have a personal history of premature CHD (18% vs 7%; P < 0.01). Mutation+ FH patients were also more likely to present with signs of lipid impregnation: corneal arcus (7.6% vs 1.4%; P = 0.012) and tendon xanthomas (6.3% vs 0.7%; P < 0.01). Regarding treatment, 41% of mutation+ FH patients were receiving statins, compared with 17% of mutation– FH patients (P < 0.01). Twenty percent of patients with mutation+ FH were receiving high‐intensity statins (compared with 3% of patients with mutation– FH), 18% a moderate‐intensity statin (compared with 10%), and 2.8% a low‐intensity statin (compared with 4%).
The lipid profile was more atherogenic in patients with mutation+ FH, with higher total cholesterol (327 ± 79 mg/dL vs 302 ± 46 mg/dL; P < 0.01), higher LDL‐C (254 ± 69 mg/dL vs 218 ± 35 mg/dL; P < 0.01), and lower HDL‐C (53 ± 14 mg/dL vs 58 ± 17 mg/dL; P < 0.01). Triglycerides were also lower (P < 0.01) in patients with mutation+ FH (90 mg/dL [interquartile range, 68–137] vs 110 mg/dL [interquartile range, 82–174]). Lipoprotein(a) levels were not significantly different between mutation+ and mutation– FH patients, and glomerular filtration rate was higher in mutation+ FH patients.
Despite the more atherogenic nonlipid CV profile of patients with mutation– FH, the age of onset of CHD was earlier in patients with mutation+ FH (48 y vs 56 y, respectively; P = 0.026). This age difference was not significant when restricted to men (48 y vs 50 y; P = 0.86) but was significant when restricted to women (48 y vs 60 y; P < 0.01).
3.4. Distribution of mutations according to DLCN score and discriminative ability of the DLCN with the area under the ROC curve
Thirty‐five percent (58/167) of patients with a DLCN score of 6 to 8 (likely FH) and 77% (114/149) of patients with a score > 8 (definite FH) showed a positive mutation. A DLCN score > 8 (definite FH) discriminated the presence of a mutation with a ROC area under the curve (AUC) of 0.70 (95% confidence interval [CI]: 0.65‐0.74). Using only a corrected LDL‐C level > 330 mg/dL, the AUC was 0.59 (95% CI: 0.56‐0.62).
3.5. Multivariate analyses
3.5.1. Predictors of a pathogenic mutation
In multivariate analysis, we found that age, personal coronary history, LDL‐C, HDL‐C, and triglycerides were significantly associated with the presence of a positive mutation (Table 3).
Table 3.
Predictors of the presence of a pathogenic mutation in multivariate analysis
| Variables | OR | P Value > z | 95% CI |
|---|---|---|---|
| Age, y | 0.96 | <0.01 | 0.95‐0.98 |
| History of premature CHD, <55 y men, 60 y women | 3.02 | <0.01 | 1.35‐6.76 |
| Premature corneal arcus, <45 y | 4.04 | 0.097 | 0.78‐20.98 |
| Tendon xanthomas | 4.70 | 0.161 | 0.54‐40.96 |
| LDL‐C > 330 mg/dL | 25.2 | <0.01 | 3.01‐204.85 |
| HDL‐C > 50 mg/dL | 0.45 | <0.01 | 0.25‐0.81 |
| TG 100 mg/dL (for an increase of 100 mg/dL) | 0.43 | <0.01 | 0.27‐0.68 |
Abbreviations: CHD, coronary heart disease; CI, confidence interval; DM, diabetes mellitus; HDL‐C, high‐density lipoprotein cholesterol; HTN, hypertension; LDL‐C, low‐density lipoprotein cholesterol; Lp(a), lipoprotein(a); MDRD, Modification of Diet in Renal Disease; OR, odds ratio; TG, triglycerides.
Variables initially included in the model were age, sex, smoker status, DM, HTN, previous history of premature (<55 y men, <60 y women) CHD, premature corneal arcus (<45 y), tendon xanthoma, first‐degree relative with premature CHD (<55 y men, <60 y women), first‐degree relative with known LDL‐C > 95th percentile, LDL‐C, HDL‐C, TG, Lp(a), and MDRD.
After adjusting for classic CV risk factors, the DLCN score (1‐point increment) remained independently predictive of a positive mutation (odds ratio: 1.25, 95% CI: 1.15–1.35, P < 0.01).
3.5.2. Predictive factors of premature coronary disease
After adjusting for classic CV risk factors, we found that the presence of a positive mutation was significantly associated with premature coronary disease (odds ratio: 3.0, 95% CI: 1.38–6.55, P < 0.01; Table 4).
Table 4.
Predictors of premature CHD in FH patients under multivariate analysis
| Variable | OR | P Value > z | 95% CI |
|---|---|---|---|
| Confirmed mutation | 3.00 | <0.01 | 1.38‐6.55 |
| Age, y | 1.07 | <0.01 | 1.04‐1.10 |
| LDL‐C > 330 mg/dL | 3.06 | 0.04 | 1.03‐9.11 |
| HDL‐C > 50 mg/dL | 0.35 | <0.01 | 0.17‐0.73 |
Abbreviations: CHD, coronary heart disease; CI, confidence interval; DM, diabetes mellitus; FH, familial hypercholesterolemia; HDL‐C, high‐density lipoprotein cholesterol; HTN, hypertension; LDL‐C, low‐density lipoprotein cholesterol; Lp(a), lipoprotein(a); MDRD, Modification of Diet in Renal Disease; OR, odds ratio; TG, triglycerides.
Variables initially included in the model were age, sex, smoker status, DM, HTN, previous history of premature (<55 y men, <60 y women) CHD, first‐degree relative with premature CHD (<55 y men, <60 y women), LDL‐C, HDL‐C, TG, Lp(a), and MDRD.
4. DISCUSSION
This study compares the CV profile of mutation+ heterozygous FH patients and mutation– FH patients. We identified a causative mutation in only 54.9% of patients, which is comparable with other studies on the subject.22, 23, 24 To our knowledge, our study is the first to assess the respective impact of the DLCN score, LDL‐C levels, and genetic status on premature CHD in FH.
When analyzing the distribution of mutations according to DLCN score, only 77% of patients with definite FH had a positive mutation, which is comparable with the German study of Grenkowitz et al. with 71.1%,16 but lower than the Italian study of Bertolini et al with 91.9%.25 The ability of the DLCN to discriminate the presence of a mutation in our population (AUC = 0.70) is comparable to its ability in the British population26 (AUC = 0.72), but lower than in the German population16 (AUC = 0.789). The discrimination capacity based solely on LDL‐C level was poorer, with an AUC of 0.59. This differs from the German study, where LDL‐C level was a better discriminator than the DLCN (0.799 vs 0.789, respectively).16
We highlighted the greater severity of coronary disease in patients with mutation+ FH, whose CHD risk was >3× higher and who had an earlier age of onset of CHD. Several studies have shown similar results.27, 28
Khera et al12 showed that, compared with a reference population with LDL‐C < 130 mg/dL and no mutation, hypercholesterolemic patients (LDL‐C > 190 mg/dL) with a positive mutation had a 22‐fold increased risk for CHD, whereas LDL‐C > 190 mg/dL and no FH mutation was associated with a 6‐fold higher risk.
Ahmad et al.9 also showed clinical and biological results similar to ours and observed premature coronary disease in mutation+ women at an age of 44 years vs 52 years in women with unexplained FH. We also found an earlier age of CHD onset in mutation+ patients (48 y vs 56 y in patients with mutation– FH; P = 0.02). Interestingly, when the population was stratified by sex, we found the same result as Ahmad et al, with a significant difference in age of CHD onset between women with mutation+ and mutation– FH (48 y vs 60 y; P < 0.01) and a nonsignificant difference for men (48 y vs 50 y; P = 0.86).
In mutation+ patients, we observed no significant difference between men and women for age of onset of CHD. The presence of the mutation appears to cancel the protective hormonal effect in young women who are not menopausal. A genetic explanation is possible. We know, for example, that the contribution of the apoE polymorphism differs by sex.29 Premature disease in women with FH may also be related to statin therapy. Neil et al. showed that this therapy was more effective in reducing CHD mortality in women than in men.30
Tada et al11 also found that CV risk was greater in the case of a positive mutation than in an absence of mutation, although the greater risk was modulated by the presence of clinical signs of FH. In clinical practice, it is useful to be able to classify patients with FH according to severity13, 31, 32, 33, 34 to give the most aggressive treatment to the patients most at risk.30, 35 Going beyond LDL‐C and the clinical signs of FH, integration of genetic data would improve assessment of the severity of these patients' disease and they could be offered more appropriate treatment.
4.1. Study limitations
This study, carried out in a single center, has some inherent limitations. Mutations of other genes, such as APOE and STAP1, have been associated with mutation+ FH.36, 37 Another limitation is the selection of patients. We chose an LDL‐C level > 190 mg/dL for adults and >160 mg/dL for patients age < 18 years.12, 38, 39 Regarding clinical examination of patients, looking for a corneal arcus or xanthelasma is relatively easy, but the clinical search for a tendon xanthoma is difficult. When Achilles tendon sonography is performed,40 Achilles tendon xanthomas were detected by physical examination in 27.6% of subjects and by sonography in 56.6% of subjects.
5. CONCLUSION
In this population of patients with FH, the presence of a pathogenic mutation was associated with a more atherogenic lipid profile, a 3‐fold greater risk of premature CHD, as well as earlier onset of premature CHD than in the absence of a genetically proven mutation.
Conflicts of interest
Jean Ferrières has received grants and lecture fees from Amgen, Merck, and Sanofi. The authors declare no other potential conflicts of interest.
Séguro F, Rabès J‐P, Taraszkiewicz D, Ruidavets J‐B, Bongard V, Ferrières J. Genetic diagnosis of familial hypercholesterolemia is associated with a premature and high coronary heart disease risk. Clin Cardiol. 2018;41:385–391. 10.1002/clc.22881
REFERENCES
- 1. Nordestgaard BG, Chapman MJ, Humphries SE, et al. Familial hypercholesterolaemia is underdiagnosed and undertreated in the general population: guidance for clinicians to prevent coronary heart disease: consensus statement of the European Atherosclerosis Society. Eur Heart J. 2013;34:3478a–3490a. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2. Ferrières J, Lambert J, Lussier‐Cacan S, et al. Coronary artery disease in heterozygous familial hypercholesterolemia patients with the same LDL receptor gene mutation. Circulation. 1995;92:290–295. [DOI] [PubMed] [Google Scholar]
- 3. Benn M, Watts GF, Tybjaerg‐Hansen A, et al. Familial hypercholesterolemia in the Danish general population: prevalence, coronary artery disease, and cholesterol‐lowering medication [published correction appears in J Clin Endocrinol Metab. 2014;99:4758–4759]. J Clin Endocrinol Metab. 2012;97:3956–3964. [DOI] [PubMed] [Google Scholar]
- 4. Catapano AL, Lautsch D, Tokgözoglu L, et al. Prevalence of potential familial hypercholesteremia (FH) in 54 811 statin‐treated patients in clinical practice. Atherosclerosis. 2016;252:1–8. [DOI] [PubMed] [Google Scholar]
- 5. Benn M, Watts GF, Tybjaerg‐Hansen A, et al. Mutations causative of familial hypercholesterolaemia: screening of 98 098 individuals from the Copenhagen General Population Study estimated a prevalence of 1 in 217. Eur Heart J. 2016;37:1384–1394. [DOI] [PubMed] [Google Scholar]
- 6. Catapano AL, Graham I, De Backer G, et al. 2016 ESC/EAS Guidelines for the Management of Dyslipidaemias. Eur Heart J. 2016;37:2999–3058. [DOI] [PubMed] [Google Scholar]
- 7. Talmud PJ, Shah S, Whittall R, et al. Use of low‐density lipoprotein cholesterol gene score to distinguish patients with polygenic and monogenic familial hypercholesterolaemia: a case‐control study. Lancet. 2013;381:1293–1301. [DOI] [PubMed] [Google Scholar]
- 8. Futema M, Shah S, Cooper JA, et al. Refinement of variant selection for the LDL cholesterol genetic risk score in the diagnosis of the polygenic form of clinical familial hypercholesterolemia and replication in samples from 6 countries. Clin Chem. 2015;61:231–238. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Ahmad Z, Li X, Wosik J, et al. Premature coronary heart disease and autosomal dominant hypercholesterolemia: increased risk in women with LDLR mutations. J Clin Lipidol. 2016;10(1):101–108.e3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Sharifi M, Higginson E, Bos S, et al. Greater preclinical atherosclerosis in treated monogenic familial hypercholesterolemia vs. polygenic hypercholesterolemia. Atherosclerosis. 2017;263:405–411. 10.1016/j.atherosclerosis.2017.05.015. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Tada H, Kawashiri MA, Nohara A, et al. Impact of clinical signs and genetic diagnosis of familial hypercholesterolaemia on the prevalence of coronary artery disease in patients with severe hypercholesterolaemia. Eur Heart J. 2017;38:1573–1579. [DOI] [PubMed] [Google Scholar]
- 12. Khera AV, Won HH, Peloso GM, et al. Diagnostic yield and clinical utility of sequencing familial hypercholesterolemia genes in patients with severe hypercholesterolemia. J Am Coll Cardiol. 2016;67:2578–2589. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Béliard S, Millier A, Carreau V, et al; French FH Registry Group . The very high cardiovascular risk in heterozygous familial hypercholesterolemia: analysis of 734 French patients. J Clin Lipidol. 2016;10(5):1129–1136.e3. [DOI] [PubMed] [Google Scholar]
- 14. Bourbon M, Alves AC, Alonso R, et al. Mutational analysis and genotype‐phenotype relation in familial hypercholesterolemia: the SAFEHEART registry. Atherosclerosis. 2017;262:8–13. [DOI] [PubMed] [Google Scholar]
- 15. Pérez de Isla L, Alonso R, Mata N, et al; SAFEHEART Investigators . Coronary heart disease, peripheral arterial disease, and stroke in familial hypercholesterolaemia: insights from the SAFEHEART Registry (Spanish Familial Hypercholesterolaemia Cohort Study). Arterioscler Thromb Vasc Biol. 2016;36:2004–2010. [DOI] [PubMed] [Google Scholar]
- 16. Grenkowitz T, Kassner U, Wühle‐Demuth M, et al. Clinical characterization and mutation spectrum of German patients with familial hypercholesterolemia. Atherosclerosis. 2016;253:88–93. [DOI] [PubMed] [Google Scholar]
- 17. Cournot M, Taraszkiewicz D, Cambou JP, et al. Additional prognostic value of physical examination, exercise testing, and arterial ultrasonography for coronary risk assessment in primary prevention. Am Heart J. 2009;158:845–851. [DOI] [PubMed] [Google Scholar]
- 18. Séguro F, Bongard V, Bérard E, et al. Dutch Lipid Clinic Network low‐density lipoprotein cholesterol criteria are associated with long‐term mortality in the general population. Arch Cardiovasc Dis. 2015;108:511–518. [DOI] [PubMed] [Google Scholar]
- 19. Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low‐density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem. 1972;18:499–502. [PubMed] [Google Scholar]
- 20. Stone NJ, Robinson JG, Lichtenstein AH, et al; American College of Cardiology/American Heart Association Task Force on Practice Guidelines . 2013 ACC/AHA guideline on the treatment of blood cholesterol to reduce atherosclerotic cardiovascular risk in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines [published correction appears in Circulation. 2014;129(25 suppl 2):S46–S48]. Circulation. 2014;129(25 suppl 2):S1–S45. [DOI] [PubMed] [Google Scholar]
- 21. Rabès JP, Varret M, Saint‐Jore B, et al. Familial ligand‐defective apolipoprotein B‐100: simultaneous detection of the ARG3500‐‐>GLN and ARG3531‐‐>CYS mutations in a French population. Hum Mutat. 1997;10:160–163. [DOI] [PubMed] [Google Scholar]
- 22. Palacios L, Grandoso L, Cuevas N, et al. Molecular characterization of familial hypercholesterolemia in Spain. Atherosclerosis. 2012;221:137–142. [DOI] [PubMed] [Google Scholar]
- 23. Moorjani S, Roy M, Gagné C, et al. Homozygous familial hypercholesterolemia among French Canadians in Québec Province. Arteriosclerosis. 1989;9:211–216. [DOI] [PubMed] [Google Scholar]
- 24. Ahmad Z, Adams‐Huet B, Chen C, et al. Low prevalence of mutations in known loci for autosomal dominant hypercholesterolemia in a multiethnic patient cohort. Circ Cardiovasc Genet. 2012;5:666–675. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25. Bertolini S, Pisciotta L, Rabacchi C, et al. Spectrum of mutations and phenotypic expression in patients with autosomal dominant hypercholesterolemia identified in Italy. Atherosclerosis. 2013;227:342–348. [DOI] [PubMed] [Google Scholar]
- 26. Futema M, Whittall RA, Kiley A, et al. Analysis of the frequency and spectrum of mutations recognised to cause familial hypercholesterolaemia in routine clinical practice in a UK specialist hospital lipid clinic. Atherosclerosis. 2013;229:161–168. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27. Marduel M, Carrié A, Sassolas A, et al. Molecular spectrum of autosomal dominant hypercholesterolemia in France. Hum Mutat. 2010;31:E1811–1824. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28. Al‐Khateeb A, Zahri MK, Mohamed MS, et al. Analysis of sequence variations in low‐density lipoprotein receptor gene among Malaysian patients with familial hypercholesterolemia. BMC Med Genet. 2011;12:40. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29. Ferrières J, Sing CF, Roy M, et al. Apolipoprotein E polymorphism and heterozygous familial hypercholesterolemia: sex‐specific effects. Arterioscler Thromb Vasc Biol. 1994;14:1553–1560. [DOI] [PubMed] [Google Scholar]
- 30. Neil A, Cooper J, Betteridge J, et al. Reductions in all‐cause, cancer, and coronary mortality in statin‐treated patients with heterozygous familial hypercholesterolaemia: a prospective registry study. Eur Heart J. 2008;29:2625–2633. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31. Santos RD, Gidding SS, Hegele RA, et al; International Atherosclerosis Society Severe Familial Hypercholesterolemia Panel . Defining severe familial hypercholesterolaemia and the implications for clinical management: a consensus statement from the International Atherosclerosis Society Severe Familial Hypercholesterolemia Panel. Lancet Diabetes Endocrinol. 2016;4:850–861. [DOI] [PubMed] [Google Scholar]
- 32. Besseling J, Kindt I, Hof M, et al. Severe heterozygous familial hypercholesterolemia and risk for cardiovascular disease: a study of a cohort of 14 000 mutation carriers. Atherosclerosis. 2014;233:219–223. [DOI] [PubMed] [Google Scholar]
- 33. Paquette M, Dufour R, Baass A. The Montreal‐FH‐SCORE: a new score to predict cardiovascular events in familial hypercholesterolemia. J Clin Lipidol. 2017;11:80–86. [DOI] [PubMed] [Google Scholar]
- 34. Gallo A, Giral P, Carrié A, et al. Early coronary calcifications are related to cholesterol burden in heterozygous familial hypercholesterolemia. J Clin Lipidol. 2017;11(3):704–711.e2. [DOI] [PubMed] [Google Scholar]
- 35. Besseling J, Hovingh GK, Huijgen R, et al. Statins in familial hypercholesterolemia: consequences for coronary artery disease and all‐cause mortality. J Am Coll Cardiol. 2016;68:252–260. [DOI] [PubMed] [Google Scholar]
- 36. Marduel M, Ouguerram K, Serre V, et al. Description of a large family with autosomal dominant hypercholesterolemia associated with the APOE p.Leu167del mutation. Hum Mutat. 2013;34:83–87. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37. Fouchier SW, Dallinga‐Thie GM, Meijers JC, et al. Mutations in STAP1 are associated with autosomal dominant hypercholesterolemia. Circ Res. 2014;115:552–555. [DOI] [PubMed] [Google Scholar]
- 38. Perak AM, Ning H, de Ferranti SD, et al. Long‐term risk of atherosclerotic cardiovascular disease in US adults with the familial hypercholesterolemia phenotype. Circulation. 2016;134:9–19. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39. Wald DS, Bestwick JP, Morris JK, et al. Child‐parent familial hypercholesterolemia screening in primary care. N Engl J Med. 2016;375:1628–1637. [DOI] [PubMed] [Google Scholar]
- 40. Jarauta E, Junyent M, Gilabert R, et al. Sonographic evaluation of Achilles tendons and carotid atherosclerosis in familial hypercholesterolemia. Atherosclerosis. 2009;204:345–347. [DOI] [PubMed] [Google Scholar]