Characteristics of Genetically Confirmed Familial Hypercholesterolemia in Chinese Patients with Coronary Heart Disease

doi:10.21203/rs.3.rs-5243180/v1

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Research Article

Characteristics of Genetically Confirmed Familial Hypercholesterolemia in Chinese Patients with Coronary Heart Disease

https://doi.org/10.21203/rs.3.rs-5243180/v1

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Background

Familial hypercholesterolemia (FH) is a genetically inherited disorder caused by monogenic mutations or polygenic deleterious variants. Patients with FH innate with significantly elevated risks for coronary heart disease (CHD). FH prevalence based on genetic testing in Chinese CHD patients is missing. Whether classical index of coronary atherosclerosis severity can be used as indicators of FH needs to be explored. To investigate the FH prevalence in Chinese CHD patients and the association of SYNTAX I score with FH genotype.

Methods

The monogenic and polygenic FH related genes were genotyped in 400 consecutively enrolled CHD patients. The clinical characteristics and SYNTAX I scores were analyzed in a retrospective nested case-control study.

Results

The prevalence of genetically confirmed FH in our CHD cohort was 8.75%. The cLDL-C level, SYNTAX I scores and incidences of triple vessel lesions in FH patients were significantly higher, while cLDL-C and SYNTAX I scores were independent risk factors for FH. Furthermore, cLDL-C levels of polygenic FH were significantly lower than monogenic FH, while their severity of coronary atherosclerosis was comparable.

Conclusions

Our study revealed a genetically confirmed FH prevalence of 8.75% in a Chinese CHD cohort. Additionally, the SYNTAX I score was an independent risk factor for FH. Besides, polygenic origin of FH should be taken into consideration for CHD patients suspected of FH.

Familial hypercholesterolemia

prevalence

SYNTAX I score

monogenic

polygenic

Familial hypercholesterolemia (FH) is a genetically inherited disorder affecting lipid metabolism, characterized by markedly elevated levels of low-density lipoprotein cholesterol (LDL-C) ¹. Four primary genes—LDL receptor (LDLR), apolipoprotein B (APOB), proprotein convertase subtilisin/kexin type 9 (PCSK9), and LDLR adaptor protein 1 (LDLRAP1)—are widely recognized as the pathogenic genes for FH. Mutations in these genes account for over 99% of the reported causative mutations for FH^{2, 3}. In contrast, mutations in other potential causative genes such as Apolipoprotein (APOE), signal transducing adaptor protein family 1 (STAP1), and lysosomal acid lipase (LIPA) ^4–8 are rare or contentious^{9, 10}.

Although clinical criteria exist for diagnosing FH, genetic screening is increasingly viewed as a gold standard. However, a significant proportion of clinically diagnosed FH cases cannot be genetically confirmed. Approximately 20%-30% of clinically suspected FH cases might be attributable to polygenic variants¹, termed as polygenic FH¹¹. Polygenic FH is defined using an algorithm based on a weighted score of 12 key single nucleotide polymorphisms (12-SNP) genotypes¹².

The prevalence of heterozygous FH (HeFH), defined as patients harbouring one single mutations on either allel of the four FH related genes, in the general population is estimated to be between 0.4%-0.5%¹³, with substantially higher rates (1.6–20.3%)^13–17 observed in patients with coronary heart disease (CHD). Variations in reported HeFH rates may be due to inconsistent diagnostic criteria, varying LDL-C levels considered, and the age of first CHD incidence. Notably, only a few studies on HeFH prevalence in CHD patients have been verified through genetic testing^{14, 15}, especially in the Chinese population^{14, 15}. Furthermore, none of these studies have considered polygenic FH. This study aims to investigate the prevalence of genetically diagnosed FH in Chinese patients with CHD.

The risk of myocardial infarction in FH patients is elevated by 12.5 times compared to non-FH individuals¹⁸. This increased risk can be attributed to the higher lifelong cumulative exposure to LDL-C, also known as the LDL-C burden, which is the sum of LDL-C levels multiplied by the number of years. This prolonged exposure significantly accelerates the development of atherosclerosis^{19, 20}. Furthermore, FH patients typically exhibit more severe atherosclerosis, characterized by multiple vessel diseases and more diffuse atherosclerotic lesions^{14, 21, 22}.

Previous research predominantly focused on clinically diagnosed FH patients, using diagnostic criteria such as the Dutch Lipid Clinic Network (DLCN) and Simon Broome Register (SBR), to evaluate the severity of atherosclerosis. However, there is a noticeable gap in studies examining the extent of atherosclerosis in genetically diagnosed FH patients. Therefore, our study aims to explore the correlation between genetic diagnoses of FH and the severity of coronary atherosclerosis. The severity can be quantitatively assessed using the Synergy Between Percutaneous Coronary Intervention With Taxus and Cardiac Surgery (SYNTAX) I score.

We hypothesize that the SYNTAX I score is linked with both monogenic and polygenic forms of FH. It may also serve as a predictive tool to identify FH-related variants in CHD inpatients. The use of the SYNTAX I score as a novel index could aid in the early identification, diagnosis, and treatment of FH in CHD patients, as well as facilitate cascade screening of their relatives.

2.1. Study population

A total of 400 consecutive patients with CHD were enrolled in this study from March 2019 to January 2021. All participants underwent genetic testing. Those data were accessed for research purposes at March 2023. A control group, matched for age and sex, was established from patients with positive genetic test results, using a 1:4 matching ratio (Fig. 1).

The inclusion criteria for participation were: (1) age between 18 and 85 years, (2) a diagnosis of CHD confirmed by angiography, and (3) a corrected LDL-C (cLDL-C) level exceeding 3.3 mmol/L (which is above the diagnosis criteria of hypercholesterolemia) or DLCN criteria score of more than 3 points, indicating at least a “Possible FH” according to DLCN criteria. Exclusion criteria included any of the following conditions: severe renal insufficiency (estimated glomerular filtration rate < 50 ml/min/1.73 m²), thyroid dysfunction, severe liver insufficiency (evidenced by alanine transaminase or aspartate aminotransferase levels exceeding three times the normal upper limit), systemic inflammatory diseases, myelomatosis, and other conditions leading to secondary hyperlipidemia or influencing the use of lipid-lowering drugs. This study adhered to the principles of the Declaration of Helsinki and received approval from the Beijing Chaoyang Hospital Ethics Committee (Ethics number: 2021-Sec-513). Written informed consent was obtained from all participants.

2.2. Clinical diagnosis of FH.

The clinical diagnosis of FH was determined using the DLCN criteria²³, excluding DNA analysis. The cLDL-C was defined as the highest value recorded before the initiation of lipid-lowering treatment (LLT). This value was either obtained from the hospital’s medical system dating back to January 1, 2000, if available, or estimated based on the potency and dosage of the LLT, using the formula cLDL-C = LDL-C × correction factor²⁴.

2.3. Genetic sequencing and in silico analysis

2.3.1 Multiplex PCR and trget sequencing

Genomic DNA was extracted from a 2 ml sample of peripheral blood using a DNA extraction kit (Tiangen Biotech, Beijing, China). The concentration of the extracted DNA was measured using a Qubit™ 3.0 Fluorometer (Thermo Fisher Scientific, USA).

The four major genes associated with FH were individually synthesized into library DNA molecules. These molecules then underwent multiple rounds of PCR amplification and subsequent purification. The PCR amplification process was conducted using a ProFlex PCR System (Applied Biosystems, USA). For library preparation, the MultipSeq® Custom Panel (Cat: IGMU209V1) from iGeneTech Bioscience (Beijing, China) was employed, adhering to the manufacturer’s standard protocols. Sequencing by synthesis was carried out on the Illumina NovaSeq 6000 System platform.

2.3.2 Sanger sequencing

Specific primers for 12-SNP sites associated with polygenic FH were designed, resulting in 12 primer pairs. These primers were used to amplify the target fragments of the sample genomic DNA using 2×Taq MasterMix (Dye) reagent (CoWin Biosciences, Jiangsu, China). Following PCR amplification, the products underwent purification.

For sequencing, the BigDye™ Terminator v3.1 Cycle Sequencing Kit (Applied Biosystems, USA) was employed alongside the specific primers to synthesize DNA molecules. The sequencing process was conducted using an ABI 3730XL Genetic Analyzer. Additionally, Sanger sequencing was utilized to validate any novel mutations discovered in the target sequencing process. This approach is robust in confirming the presence and nature of genetic variations pertinent to polygenic FH.

2.3.3 Data analysis

The bioinformatics analysis of the multiplex PCR sequencing data was conducted using the “Bestnovo Cloud Gene Detection and Automatic Analysis Platform”. The raw image data generated by the Illumina NovaSeq 6000 system were converted into sequence data via Base Calling and stored in the FASTQ file format. This sequencing data was then aligned with the human genome reference sequence (hg19) from the UCSC database using Burrows-Wheeler Aligner (BWA) software. The coverage of the target region and the quality of sequencing were assessed.

Variant identification was performed using the HaplotypeCaller tool from the Genome Analysis Toolkit (GATK) software. Identified variants were filtered based on stringent criteria, and ANNOVAR software was used to provide relevant annotation information. For 12-SNP types, Sanger sequencing results were analyzed using Chromas 2.4.1 software (Technelysium). This comprehensive approach ensured the accurate identification and annotation of genetic variants relevant to the study.

2.3.4 Genetic analysis report

Genetic analysis was performed for all participants at four exon mutation loci—namely LDLR, APOB, PCSK9, and LDLRAP1—as well as for 12-SNP detailed in Supplementary Table 1. A mutation locus was classified as pathogenic if it was listed in disease-specific databases such as the Human Gene Mutation Database (HGMD) and ClinVar. For loci not recorded in these databases and with an allele frequency of less than 0.01 in population databases, three common in silico analyses were employed: PolyPhen-2, Sorting Tolerant From Intolerant (SIFT), and Mutation Taster. To be deemed pathogenic, non-synonymous mutations needs to meet at least two of the following three criteria: (1) classified as probably damaging (D) or possibly damaging (P) in PolyPhen-2²⁵, (2) deemed deleterious (D) in SIFT²⁶, and (3) identified as disease causing automatic (A) or disease causing (D) in Mutation Taster²⁷. Participants were categorized based on decile ranges of their 12-SNP weighted scores: a score of ≤ 0.73 points indicated low risk for polygenic hypercholesterolemia²⁸; a score between > 0.73 and < 1.16 points indicated medium risk; and a score of ≥ 1.16 points indicated high risk. All loci were validated through Sanger sequencing, and interpretations of the reports were conducted under the supervision of a sophisticated geneticist.

A diagnosis of FH was made if patients exhibited at least one of the four major monogenic pathogenic mutations or had a 12-SNP weighted score of ≥ 1.16 points²⁸. Conversely, a diagnosis of non-FH was assigned to patients lacking monogenic pathogenic mutations and with a 12-SNP weighted score of < 0.73 points.

2.4. Laboratory measurement

On the first day following admission, 5 mL of venous blood samples which were collected from fasting patients and analyzed with a Dimension RxLMax™ automated analyzer. All biochemical indices, including the cLDL-C levels, were measured using a Hitachi 7600 automated analyzer. The cLDL-C levels were either retrieved from the hospital’s medical system, if available, or estimated using a correction factor. This process ensured accurate and standardized measurement of biochemical parameters critical for the study.

2.5. Coronary features analysis

Patients with CHD were identified based on the presence of coronary stenosis: ≥50% in the left main coronary artery or ≥ 70% in at least one of the major coronary arteries, as determined by angiography^{29, 30}. The severity of CHD was assessed using the SYNTAX I score, calculated via a software tool available at www.SYNTAXscore.com. The SYNTAX I scores were independently calculated by two physicians, P.J.W. and L.C., and the average of these scores was used to minimize bias in the assessment. This method ensured a more objective and reliable evaluation of CHD severity in the study participants.

2.6. Statistical analysis

Data were presented as means ± standard deviation (SD) or medians (with upper and lower quartiles) for continuous variables, and as counts (percentages) for categorical variables. For quantitative data conforming to a normal distribution, the t-test was employed for comparisons between two independent groups. In cases where the data did not follow a normal distribution, the Mann-Whitney U test was used instead. The Kruskal-Wallis test was used to compare multiple independent variables, with using Bonferroni correction, significance threshold was 0.0167 (0.05/3). Qualitative data were analyzed using the χ2-test, supplemented by Fisher’s exact probability test for correction as necessary.

Univariate and multivariate logistic regression analyses were conducted to identify independent factors associated with FH. Continuous independent factors were transformed into categorical variables using cut-off values derived from receiver operating characteristic (ROC) curve analysis. These categorical variables were then utilized to develop a new diagnostic predictive model for FH using a logistic regression model. The accuracy of the cLDL-C group, SYNTAX I group, and predicted probability 1 (Pred1) as predictors of FH was compared using ROC curves to obtain the area under the curve (AUC), cut-off value, sensitivity, and specificity. A p-value of < 0.05 was considered statistically significant. All statistical analyses were performed using SPSS version 26.0 software and MedCalc version 22.016 software.

Prevalence of FH in Chinese CHD patients

In this study, 400 patients with CHD were initially enrolled. Genetic testing revealed that 26 patients (6.5%) had monogenic FH as per ACMG criteria, and 9 patients (2.25%) polygenic FH. Consequently, these 35 patients (8.75%) were classified into the FH group (monogenic or high-risk polygenic FH), serving as the case group. Following adjustment for age, sex and using a matching ratio of 1:4, a control group of 140 non-FH patients was established, including 126 patients with medium-risk polygenic FH and 14 patients with low-risk polygenic FH. In total, 175 patients (83.9% of man and 17.1% of women) were included. The average age of enrolled CHD patients was 63.4 ± 9.2 years, and the mean cLDL-C level was 3.99 ± 1.01 mmol/L.

SYNTAX I score could serve as potential indicators for FH diagnosis in coronary heart disease patients

The baseline characteristics of the FH and non-FH groups are detailed in Table 1. Compared to non-FH patients, the cLDL-C level in FH patients was significantly higher (4.70 ± 1.53 mmol/L) (3.81 ± 0.74 mmol/L, P = 0.002). It is worth noting that FH patients had significantly higher SYNTAX I scores (24.0 (18.0, 34.0) vs. 17.0 (10.0, 22.0), P < 0.001) and a greater prevalence of triple vessel lesions (77.1% vs. 54.3%, P = 0.014).

Table 1

Baseline characteristics analysis of matched subset (N = 175)
Variables	FH (35)	non-FH (140)	P value
Basic informations
Age (y)	63.5 ± 9.4	63.4 ± 9.1	0.931
Male	29 (82.9%)	116 (82.9%)	1.000
BMI (kg/m²)	26.1 ± 3.0	26.7 ± 4.4	0.409
Smoking	16 (45.7%)	52 (37.1%)	0.352
HR (BPM)	73.0 ± 8.5	75.1 ± 12.4	0.348
SBP (mmHg)	138.3 ± 18.4	137.7 ± 18.1	0.850
DBP (mmHg)	76.6 ± 10.6	77.8 ± 11.3	0.581
Tendon xanthoma	0 (0.0%)	0 (0.0%)	-
Arcus corneae	0 (0.0%)	0 (0.0%)	-
Family history of premature ASCVD	8 (22.9%)	42 (30.0%)	0.403
History LLT	22 (62.9%)	90 (64.3%)	0.875
Comorbidities
Premature ASCVD	14 (40.0%)	77 (55.0%)	0.112
Previous MI	6 (17.1%)	20 (14.3%)	0.671
PCI history	10 (28.6%)	28 (20.0%)	0.271
CABG history	1 (2.9%)	2 (1.4%)	0.490
Stroke	7 (20.0%)	19 (13.6%)	0.339
PVD	4 (11.4%)	6 (4.3%)	0.115
Hypertension	25 (71.4%)	102 (72.9%)	0.865
Diabetes mellitus	18 (51.4%)	59 (42.1%)	0.322
Heart failure	7 (20.0%)	16 (11.4%)	0.260
Hyperuricemia	2 (5.7%)	9 (6.4%)	1.000
Biological data
TG (mmol/L)	1.24 (0.88, 1.65)	1.26 (0.97, 2.01)	0.495
Treated LDL-C (mmol/L)	3.14 ± 2.07	2.44 ± 0.95	0.059
Corrected LDL-C (mmol/L)	4.70 ± 1.53	3.81 ± 0.74	0.002
Lp (a) (mg/dL)	18.10 (11.00, 28.20)	16.95 (9.83, 33.10)	0.761
HbA1C (%)	6.83 ± 1.26	6.83 ± 1.23	0.985
UA (µmol/L)	383.0 (317.0, 440.0)	344.0 (285.0, 410.8)	0.140
eGFR (ml/min/1.73m²)	93.9 (83.7, 104.7)	95.0 (85.0, 101.0)	0.840
Imaging indexs
IMT	2 (5.7%)	17 (12.1%)	0.372
Carotid plaque	5 (14.3%)	15 (10.7%)	0.557
SYNTAX I score	24.0 (18.0, 34.0)	17.0 (10.0, 22.0)	<0.001
Triple vessel lesions	27 (77.1%)	76 (54.3%)	0.014
FH related indicators
12-SNP score	0.99 (0.58, 1.16)	0.98 (0.90, 1.04)	0.655
DLCN score 1*	2 (1, 3)	2 (0, 3)	0.350
DLCN score 2✝	9 (2, 11)	2 (0, 3)	<0.001
FH indicates familial hypercholesterolemia; BMI, body mass index; HR, heart rate; BPM, beats per minute; BP, blood pressure; SBP, systolic blood pressure; DBP, diastolic blood pressure; ASCVD, atherosclerotic cardiovascular disease; LLT, lipid-lowering treatment; MI, myocardial infarction; PCI, percutaneous coronary intervention; CABG, coronary artery bypass grafting; PVD, peripheral vascular disease; TG, triglycerides; LDL-C, low-density lipoprotein cholesterol; Lp (a), lipoprotein (a); HbA1C, glycated hemoglobin; UA, uric acid; eGFR, estimated glomerular filtration rate; IMT, intima-media thickness; SYNTAX, synergy between percutaneous coronary intervention with taxus and cardiac surgery; SNP, single nucleotide polymorphism and DLCN, dutch lipid clinic network.
* DLCN score 1: not include DNA analysis score in criteria.
✝DLCN score 2: include DNA analysis score in criteria.

Subsequent logistic regression analysis was conducted to determine whether the parameters showing significant differences were independently associated with FH diagnosis. The univariate logistic regression analysis (Table 2) revealed that both the cLDL-C concentration (Odds Ratio [OR]: 2.204, P = 0.010), the SYNTAX I score (OR: 1.145, P < 0.001) as well as the presence of triple vessel lesions (OR: 2.842, P < 0.017) were significantly associated with FH. These associations persisted in the multivariate logistic regression analysis, except for the presence of triple vessel lesions (P = 0.878) (Table 2). The cLDL-C concentration (OR: 1.778, P < 0.001) and the SYNTAX I score (OR: 1.124, P < 0.001) maintained their statistical significance, thus confirming them as independent risk factors for an FH diagnosis. This analysis underscores the importance of these parameters in the diagnostic process for FH.

Table 2

Logistic regression analysis of the influence of variables on the monogenic FH (FH = 35)
	Univariate logistic regression			Multivariate logistic regression
Variables	β	OR (95% CI)	P	β	OR (95% CI)	P
Corrected LDL-C	0.790	2.204 (1.476–3.292)	< 0.001	0.576	1.778 (1.149–2.752)	0.010
SYNTAX I score	0.135	1.145 (1.083–1.211)	< 0.001	0.117	1.124 (1.059–1.193)	< 0.001
Triple vessel lesions
No	Reference			Reference
Yes	1.045	2.842 (1.207–6.691)	0.017	0.078	1.081 (0.400-2.915)	0.878
FH indicates familial hypercholesterolemia; LDL-C, low-density lipoprotein cholesterol; and SYNTAX, synergy between percutaneous coronary intervention with taxus and cardiac surgery.

The study utilized ROC curve analysis to evaluate the predictive power of the cLDL-C level and SYNTAX I score in diagnosing FH (Fig. 2a). The AUC for the cLDL-C level was 0.667 (P = 0.0023), with a determined cut-off value of 4.02 mmol/L for identifying carriers of FH variants (monogenic or polygenic FH). This cut-off value yielded a sensitivity of 57.14% and a specificity of 75.00%. The AUC for the SYNTAX I score was 0.759 (P < 0.001), with a cut-off value of 29.5, and demonstrated a sensitivity of 48.57% and a specificity of 100.00%. There was no significant difference between the AUCs of these two indicators (P = 0.1953).

Based on the integer part of the cut-off values, the two predictors were converted from continuous to categorical variables (defined as cLDL-C ≥ 4 mmol/L = 1, cLDL-C < 4 mmol/L = 0, SYNTAX I score ≥ 29 = 1, SYNTAX I score < 29 = 0). A new multivariate logistic regression analysis was then performed to establish a predictive probability model. Both the cLDL-C group (P < 0.019) and the SYNTAX I group (P < 0.001) were statistically significant. The Pred1 formula was: Y = -2.491 + 1.140 × cLDL-C group + 4.098 × SYNTAX I group.

Figure 2b presented the ROC curve analysis of the cLDL-C group, SYNTAX I group, and Pred1 in predicting FH. The AUC for Pred1 was 0.795 (P < 0.001), with a cut-off value of 0.21, and a sensitivity and specificity of 48.57% and 98.57%, respectively. The AUC of Pred1 was significantly higher than that of the cLDL-C group (P < 0.001). However, there were no significant differences between the Pred1 and SYNTAX I group (P = 0.0738), or between the cLDL-C group and SYNTAX I group (P = 0.1469).

Polygenic FH patients share with monogenic FH patients regarding CHD risk notwithstanding lower cLDL-C levels

Within the FH group, monogenic FH patients had significantly higher cLDL-C levels (4.99 ± 1.63 vs 3.85 ± 0.73, P = 0.008), as compared to polygenic FH patients. However, their SYNTAX I scores were similar [23.3 (18.0, 32.1) vs 30.0 (16.5, 48.3), P = 0.516] (Table 3), suggesting similar pro-atherosclerotic tendencies between the two groups.

Table 3

Characteristics analysis of monogenic and polygenic FH groups (N = 35)
Variables	monogenic FH (26)	polygenic FH (9)	P value
Corrected LDL-C (mmol/L)	4.99 ± 1.63	3.85 ± 0.73	0.008
SYNTAX I score	23.3 (18.0, 32.1)	30.0 (16.5, 48.3)	0.516
DLCN score 1*	2.0 (1.0, 4.0 )	1.0 (0.0, 2.0)	0.046
DLCN score 2✝	10.0 (9.0, 12.3)	1.0 (0.0, 2.0)	<0.001
FH indicates familial hypercholesterolemia; LDL-C, low-density lipoprotein cholesterol; SYNTAX, synergy between percutaneous coronary intervention with taxus and cardiac surgery; and DLCN, dutch lipid clinic network.
* DLCN score 1: not include DNA analysis score in criteria.
✝DLCN score 2: include DNA analysis score in criteria.

Additionally, while the cLDL-C levels of high-risk polygenic FH patients were not significantly higher than those of non-FH patients, polygenic FH group exhibited significantly higher SYNTAX I scores than non-FH groups (P = 0.006 and P = 0.003, respectively, lower than the Bonferroni correctehd threshold of 0.0167) (Table 4a and 4b). This indicates that polygenic FH patients indeed have a higher risk than non-FH patients regarding pro-atherosclerotic tendencies.

Table 4

a. Characteristics of different risk groups of polygenic FH (N = 149)
Variables	Corrected LDL-C (mmol/L)	SYNTAX I score
high risk (9)	3.85 ± 0.73	30.0 (16.5, 48.3)
middle risk (126)	3.84 ± 0.75	17.0 (10.0, 22.6)
low risk (14)	3.58 ± 0.61	14.0 (7.8, 20.3)
P value	0.653	0.008
FH indicates familial hypercholesterolemia; LDL-C, low-density lipoprotein cholesterol; and SYNTAX, synergy between percutaneous coronary intervention with taxus and cardiac surgery.

Table 4

b. Comparison of SYNTAX I score between three risk groups of polygenic FH (N = 149)
Variables		P value*
high risk vs. middle risk		0.006
high risk vs. low risk		0.003
middle risk vs. low risk		0.257
FH indicates familial hypercholesterolemia; and SYNTAX, synergy between percutaneous coronary intervention with taxus and cardiac surgery.
*P value is compared with Bonferroni corrected threshold of 0.0167.

This study delineates the clinical characteristics of FH in patients with CHD, focusing on genetically diagnosed cases. Initially, we report the prevalence of FH, including both monogenic and polygenic forms, in a Chinese CHD cohort. Furthermore, leveraging coronary angiography data, we explore the relationship between the SYNTAX I score and FH diagnosis. Notably, patients with FH exhibited significantly more severe atherosclerosis, as evidenced by higher SYNTAX I scores and a greater incidence of triple vessel disease. Additionally, the study highlights the similar severity of atherosclerosis in polygenic FH patients compared to those with monogenic FH, underscoring the necessity of further evaluating polygenic FH in patients without mutations in the classical FH-related genes.

The prevalence of FH in our CHD cohort, at 8.75% (including polygenic cases), exceeds previously reported figures. However, these variations in prevalence are attributable to differing diagnostic criteria. A meta-analysis encompassing over 10 million subjects reported FH prevalence rates of 3.2% in CHD, rising to 6.7% in cases of premature CHD¹³. The inconsistency in diagnostic criteria, which often blend clinical and genetic assessments, complicates these findings. Genetic testing, considered more reliable than clinical diagnosis due to often ambiguous clinical histories, reveals different insights³¹. For example, tendon xanthomas, a significant component in the DLCN criteria, are infrequently evaluated in clinical practice. Moreover, the widespread use of statins over the past three decades has reduced the physical manifestations of FH, such as xanthomas¹³. Furthermore, some patients may experience premature CHD before receiving a later CHD diagnosis, potentially leading to an underestimation of the DLCN score prior to genetic testing. In line with this, Amor-Salamanca et al. reported an 8.7% prevalence of FH in a cohort of acute coronary syndrome patients using genetic testing, paralleling our findings and suggesting the need for larger cohorts for further validation³². Additionally, data on FH prevalence among Chinese CHD patients are limited, with previous studies indicating FH prevalence rates ranging from 4.4–7.6% in premature myocardial infarction cases^{15, 33}. Our study is the first to present the prevalence of genetically diagnosed FH in a general CHD patient population.

This study also observed more severe atherosclerosis in FH patients, as indicated by higher SYNTAX I scores. Additionally, FH patients exhibited more diffuse lesions, although this difference was not statistically significant following logistic regression analysis. It is well-documented that FH patients often experience more severe CHD than non-FH individuals, characterized by multiple vessel involvement²¹ and more severe atherosclerosis^{14, 22}. For instance, Ranshaka Auckle et al.²¹ demonstrated that among 498 patients with premature ST-segment-elevation myocardial infarction (STEMI), those with possible, probable, or definite FH (according to DLCN criteria) had a higher likelihood of multivessel stenosis compared to those unlikely to have FH. Similarly, Jian-Jun Li et al.¹⁴ found a positive correlation between lesion severity, as assessed by the Gensini score (GS), and the degree of clinically diagnosed FH. Michel Farnier et al.²² showed that patients with probable or definite FH had significantly higher SYNTAX scores than those unlikely to have FH in a study of 233 patients with acute myocardial infarction.

In our study, genetic testing, which is the gold standard for diagnosing FH, was used, enhancing the validity of these associations. However, genetic testing is not routinely employed in clinical practice, leading to a low diagnosis rate of genetic FH (less than 1%)³⁴. Therefore, the SYNTAX I score could serve as a simple yet effective indicator for identifying potential FH patients, enabling physicians to initiate appropriate diagnostic procedures for FH and determine LDL-C management goals.

Our study found that monogenic and polygenic FH accounted for 74.3% and 25.7% of FH cases within CHD patients, respectively. Notably, while average LDL-C levels were higher in monogenic FH patients, SYNTAX I scores did not significantly differ between monogenic and polygenic FH patients. Moreover, SYNTAX I scores were significantly higher in polygenic FH patients compared to non-FH patients. This finding suggests that, in addition to monogenic FH, polygenic FH should not be overlooked. In clinical practice, a substantial number of patients present with significantly elevated LDL-C levels but lack monogenic pathogenic mutations¹. It is estimated that only 60–70% of patients classified as probable or definite FH according to DLCN criteria actually harbor FH-related mutations³⁵. The observation that polygenic FH patients exhibit a similar severity of atherosclerosis as monogenic FH patients underscores the importance of screening for polygenic FH in patients with probable or definite FH or CHD patients with severe atherosclerosis.

Firstly, it is important to note that not all pre-treatment LDL-C concentrations were accessible in this study. For patients without available objective pre-treatment LDL-C data, an estimated formula, as outlined in the methods section, was utilized to calculate the cLDL-C. This estimation could potentially impact the accuracy of the LDL-C levels. However, such estimation techniques are commonly accepted in cholesterol-related research and are generally considered reliable proxies for true LDL-C levels.

Secondly, the SYNTAX I score can exhibit variability due to intra-observer and inter-observer heterogeneity^35,3. However, in this study, no significant differences were observed between the SYNTAX I scores assessed by two different physicians. The use of an average SYNTAX I score value in our analysis aimed to mitigate this potential source of bias.

Lastly, it should be acknowledged that this was a single-center retrospective study. Consequently, the calculated prevalence of FH may not fully represent the broader population. Further research involving larger and more diverse cohorts is needed to validate and refine these findings.

The study revealed that the prevalence of genetically diagnosed FH patients in the cohort was 8.75%, encompassing both monogenic and polygenic forms of the condition. Furthermore, the SYNTAX I score was identified as an independent predictor of the FH genotype. Notably, patients with polygenic FH demonstrated a similar severity of atherosclerosis when compared to those with monogenic FH, indicating the importance of considering both types in the evaluation and management of patients with suspected FH.

FH: Familial hypercholesterolemia; CHD: coronary heart disease; LDLR: LDL receptor; APOB: apolipoprotein B; PCSK9: proprotein convertase subtilisin/kexin type 9; LDLRAP1: LDLR adaptor protein 1; APOE: Apolipoprotein; STAP1: signal transducing adaptor protein family 1; LIPA: lysosomal acid lipase; HeFH: heterozygous FH; DLCN: Dutch Lipid Clinic Network; SBR: Simon Broome Register; SYNTAX I: Synergy Between Percutaneous Coronary Intervention With Taxus and Cardiac Surgery I

Acknowledgements

Not applicable.

Author’s contributions

P.W and Y.D contributed to the conception and design of the work. Y.W and P.W drafted the manuscript. Y. W and C. L contributed to the data collection for the work. Y.D and W.Z contributed to the data analysis and interpretation for the work. W. Z, and Y.D critically revised the manuscript. All authors critically reviewed the manuscript and gave final approval and agree to be accountable for all aspects of work ensuring integrity and accuracy.

Funding

None.

Availability of data and materials

The datasets generated and/or analysed during the current study are not publicly available due to the restrictions of human genetics data policy of Beijing Chaoyang Hospital Ethics Committee, but are available from the corresponding author on reasonable request.

Ethics approval and consent for participate

The study protocol was approved by the ethics committee of Beijing Chaoyang Hospital, Capital Medical University and performed in accordance with the ethical standers laid down in the 1964 Declaration of Helsinki and its later amendments. Written informed consents were obtained from all participants.

Consent for publication

Not applicable.

Clinical trial number

Not applicable.

Competing interests

None .

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No competing interests reported.

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Characteristics of Genetically Confirmed Familial Hypercholesterolemia in Chinese Patients with Coronary Heart Disease

Status:

Version 1

Abstract

Background

Methods

Results

Conclusions

Figures

1. Introduction

2. Method

2.1. Study population

2.2. Clinical diagnosis of FH.

2.3. Genetic sequencing and in silico analysis

2.3.1 Multiplex PCR and trget sequencing

2.3.2 Sanger sequencing

2.3.3 Data analysis

2.3.4 Genetic analysis report

2.4. Laboratory measurement

2.5. Coronary features analysis

2.6. Statistical analysis

3. Result

4. Discussion

5. Limitations

6. Conclusions

Abbreviations

Declarations

References

Additional Declarations

Status:

Version 1