You are viewing the site in preview mode

Skip to main content

Familial hypercholesterolemia in Chinese children and adolescents: a multicenter study

Abstract

Background

Familial hypercholesterolemia (FH) is an inherited disorder mainly marked by increased low-density lipoprotein cholesterol (LDL-C) concentrations and a heightened risk of early-onset arteriosclerotic cardiovascular disease (ASCVD). This study seeks to characterize the genetic spectrum and genotype‒phenotype correlations of FH in Chinese pediatric individuals.

Methods

Data were gathered from individuals diagnosed with FH either clinically or genetically at multiple hospitals across mainland China from January 2016 to June 2024.

Results

In total, 140 children and adolescents (mean age of 6.00 years) with clinically and genetically diagnosed FH were enrolled in the study, with 87 distinct variants identified in the LDLR, APOB and PCSK9 genes. Among the variants, 11 variants were newly identified worldwide, with 9 classified as “pathogenic” or “likely pathogenic”, and 2 classified as “variants of uncertain significance”. Additionally, the 5 most common variants in the study were c.1448G > A (p.W483*), c.1879G > A (p.A627T), c.1216C > A (p.R406R), and c.1747C > T (p.H583Y) in the LDLR gene, as well as c.10579C > T (p.R3527W) in the APOB gene, accounting for 49.29% (69/140) of all patients. These variants are primarily observed in the Asian or Chinese population and are distinct from those present in Caucasian groups. In this cohort, 105 patients were diagnosed with heterozygous FH (HeFH), while 35 were diagnosed with homozygous FH (HoFH). Finally, only 28.57% of the patients (40/140) were using lipid-lowering medications with 33.33% of HoFH patients initiating treatment after the age of 8. Additionally, only 3 compound heterozygous patients (2.14%) underwent liver transplantation because of significantly high lipid levels.

Conclusion

This study reveals the variable genotypes and phenotypes of children with FH in China and illustrates that the genotypes in the Chinese population differ from those in Caucasians, providing a valuable dataset for the clinical genetic screening of FH in China. Furthermore, the older age at diagnosis and treatment highlights the underdiagnosis and undertreatment of Chinese FH pediatric patients, suggesting that early identification should be improved through lipid or genetic screening, and that more timely and regular pharmacological treatments should be implemented.

Introduction

Familial hypercholesterolemia (FH) is an autosomal inherited disorder resulting from pathogenic variants in the low-density lipoprotein (LDL) receptor (LDLR), its ligand apolipoprotein B (APOB), proprotein convertase subtilisin/kexin type 9 (PCSK9), and LDLR adaptor protein 1 (LDLRAP1) genes, which account for 85%—90%, 5%—10%, 1%−3%, and less than 1% of FH cases, respectively [1, 2]. In addition, more genes [e.g., growth hormone receptor (GHR), signal-transducing adaptor family member 1 (STAP1) and apolipoprotein E (APOE)] have been recognized as potential contributors to FH [3]. These variants impair the normal elimination of plasma LDL particles, thereby inducing significantly increased LDL cholesterol (LDL-C) concentrations over a lifetime and a considerable risk of early-onset ASCVD [4]. FH is clinically diagnosed based on phenotypic indicators such as high LDL-C levels, xanthomas, corneal arcus, early-onset ASCVD, and family history [5]. Furthermore, genetic testing is then recommended for clinically diagnosed patients or family cascade screenings of FH families [6].

FH is characterized by two forms: heterozygous HeFH) and homozygous (HoFH), depending on whether one or two pathogenic genes are present [1, 2]. HeFH is relatively common, occurring in about 1 in 311 to 500 people in the general population, whereas HoFH is extremely rare and severe, with an estimated incidence of 1 in 160,000–250,000 individuals [7,8,9]. Although the mutation spectrum and phenotype‒genotype correlations of FH have been explored, about ninety percent of adults and ninety-five percent of children remain unrecognized, and FH patients often do not receive adequate treatment worldwide [10]. Owing to the large Chinese population, there may be 5.6 million HeFH patients and approximately 5,000 HoFH patients, with only 4.2% of confirmed or likely FH patients receiving lipid-lowering therapy (LLT) [11]. The underidentification and undertreatment of FH contribute to 10% of the population suffering from myocardial infarction before the age of 50, emphasizing the urgent need for early identification and treatment of FH [12]. Therefore, the clinical characteristics, genetic variants, and genotype‒phenotype correlations in 140 FH pediatric patients and families in China were investigated between 2016 and 2024 to highlight the diagnosis and management of the orphan disease.

Materials and methods

Patients

A multicenter cohort study on pediatric patients (below the age of 18 years) diagnosed with FH both clinically and genetically was performed between January 2016 and June 2024. According to Chinese expert consensus, the enrollment criteria for the study were (1) fasting pre-treatment LDL-C concentration > 4.90 mmol/L (190 mg/dL) on the basis of two consecutive measurements; (2) fasting pre-treatment LDL-C concentration > 3.60 mmol/L (140 mg/dL) with xanthomas, corneal arcus, or premature ASCVD; (3) fasting pre-treatment LDL-C concentration > 3.60 mmol/L (140 mg/dL) with a familial history of hypercholesterolemia and/or premature ASCVD in first- or second-degree relatives; and (4) the presence of one or two pathogenic or likely pathogenic variants in the LDLR, APOB, or PCSK9 genes or two pathogenic or likely pathogenic variants in the LDLRAP1 gene through genetic testing [13]. Additionally, HoFH should be diagnosed clinically when the fasting pre-treatment LDL-C concentration is ≥ 13 mmol/L (500 mg/dL).

Additionally, patients with combined hyperlipidemia, hypertriglyceridemia, and other conditions that could induce secondary hypercholesterolemia (e.g., Cushing's syndrome, nephrotic syndrome, Wilson's disease and other definitive primary liver or kidney diseases) were excluded. The research participants consisted of individuals genetically diagnosed with HeFH and HoFH.

Clinical characteristics and laboratory investigations

Clinical data, including demographics (age and sex), clinical features (e.g., xanthomas and corneal arcus), height (m), weight (kg), physical examination findings, and personal and familial histories of dyslipidemia and ASCVD, were collected at the time of initial diagnosis. Onset age is defined as the age when xanthomas or elevated lipid levels were first detected. Diagnostic age is defined as the age when the patient was genetically diagnosed with FH. Inclusion age is defined as the age when the patient was enrolled in the study.

Total cholesterol (TC), LDL-C, high-density lipoprotein cholesterol (HDL-C), triglycerides (TG), apolipoprotein A (APOA), APOB, and lipoprotein (a) [Lp(a)] were evaluated in blood samples collected in the morning following an overnight fast. The patients also underwent Doppler echocardiography to evaluate the anatomy of the carotid artery and heart, especially the carotid intima‒media thickness (cIMT). Based on medical records and follow-up phone calls, lipid-lowering therapy data were also collected from the participants.

Genetic analysis

Patients and their first-degree relatives provided peripheral blood samples for genomic DNA extraction. The DNA was fragmented by sonication, followed by end repair and adapter attachment at both ends. After amplifying the library, the DNA fragments were captured and enriched via an exon chip and then further amplified and subjected to WES via the Illumina platform. Sanger sequencing was used to confirm the identified variant in other family members for certain patients. The human genome reference sequence hg19 was used to align the obtained DNA sequences via the Barrows–Wheeler Aligner (BWA), in order to assess the coverage and quality of sequencing in the target regions. The Guangzhou KingMed Center for Clinical Laboratory conducted the analysis.

The Leiden Open Variation Database (LOVD3), the Human Gene Mutation Database (HGMD), and ClinVar were used to check all identified variants for novelty. Predictions regarding protein structure and functional alterations were evaluated by Sorting Intolerant From Tolerant (SIFT), Polymorphism Phenotyping v2 (PolyPhen-2), and Mutation Taster.

In accordance with the recommendations of the American College of Medical Genetics (ACMG) and the classification guidelines modified by the Clinical Genome Resource (ClinGen) Familial Hypercholesterolemia Variant Curation Expert Panel [14, 15], the pathogenicity of the variants was assessed and classified as pathogenic (P), likely pathogenic (LP), variants of uncertain significance (VUS), likely benign (LB), or benign (B). Additionally, the Human Genome Variation Society (HGVS) provided guidelines for naming diverse variants. LDLR variants have been classified into “null” and "defective” categories depending on functional changes. Truncating variants, altered translation initiation sites, frameshift mutations, splice-site alterations, and large genomic rearrangements involving one or more exons are all types of “null” variants in LDLR, which lead to the production of either a completely defective or absent protein. In contrast, “defective” variants refer to missense variants that cause partial loss of function (LOF) or altered function of the receptor [8]. Given that various variant types and statuses can affect protein function differently, heterozygous patients were categorized into three groups: HeFH with APOB/PCSK9 variants, HeFH with defective LDLR variants, and HeFH with null LDLR variants. In addition, homozygous FH strains were categorized into double heterozygotes (two variants in 2 different genes), compound heterozygotes (two variants in 2 different alleles of the same gene) or true homozygotes (two variants in the same allele) [16].

Statistical analysis

SPSS software (version 26.0 for Mac; SPSS Inc., Chicago, IL, USA) was used to perform the statistical analysis. Data with a normal distribution are expressed as means ± standard deviations (means ± SDs) and were analyzed using Student's t-test or one-way ANOVA. Data with a nonnormal distribution are expressed as the medians with interquartile ranges [medians, (IQRs)] and were analyzed using the Mann‒Whitney or Kruskal‒Wallis test. The frequencies (%) of categorical variables were reported and assessed with the Chi-square test or Fisher’s exact method. In addition, multivariate logistic regression and analysis of covariance (ANCOVA) were performed to adjust for significant differences in the age at initial diagnosis. Graphics were created via GraphPad Prism 10 and MS Excel 2021. Statistical significance was deemed to be present when the P value was below 0.05.

Results

Study population

A total of 170 clinically diagnosed subjects were recruited over the past eight years. Through molecular testing, 26 individuals were diagnosed with variants in ATP-binding cassette subfamily G member 5 (ABCG5) and ATP-binding cassette subfamily G member 8 (ABCG8) was subsequently excluded from the study [17]. In addition, 4 individuals with no detectable variants were also excluded. Overall, 140 patients with identified positive variants participated in the study. This cohort consisted of patients with increased LDL-C levels and pathogenic or likely pathogenic variants, as well as patients with VUS or likely benign variants, increased LDL-C concentrations and a relevant familial history of hypercholesterolemia.

Among them, 88.57% (n = 124) were from southern China, with the majority of families coming from Zhejiang Province (n = 106, 75.70%), while the second-largest group was from the Beijing-Tianjin-Hebei region (n = 12, 8.57%).

Baseline characteristics

The baseline characteristics of the cohort (n = 140, 52.14% male) are presented in Table 1. The majority of patients (n = 101, 72.14%) visited the outpatient clinic for the first time because of elevated lipid levels discovered incidentally during laboratory investigations. Nevertheless, 29 patients (20.71%) were initially detected due to the presence of xanthomas, and 5 of them underwent skin biopsies to confirm the diagnosis, which resulted in a delay in their diagnosis. Additionally, 10 patients (7.14%) were detected through genetic testing of family members. The median age at the time of onset was 5.00 years, with the range spanning from 0.08 to 16.50 years. The diagnosis was established at an average age of 6.00 years, ranging between 0.17 and 17.00 years. Moreover, only 40.71% (57/140) of patients received an FH diagnosis before the age of 5. Among these patients, the prevalence rates of xanthoma, corneal arcus, and thickening cIMT were 25.71%, 4.28%, and 7.14%, respectively. Four individuals developed atherosclerotic deposits in the carotid arteries.

Table 1 The baseline characteristics of all patients (n = 140)

The average levels of fasting untreated lipid profiles are also presented in Table 1. Notably, LDL-C concentrations ranging from 3.6 mmol/L to 4.9 mmol/L were observed in 15.00% (21/140) of patients, which do not meet the recommended cutoff values for FH as outlined in the American Multisociety 2018 lipid guidelines [18]. At the time of inclusion in this study, 69.28% (97/140) of patients were following a low-lipid diet to lower their lipid levels, 28.57% (40/140) were using lipid-lowering medications, with the majority taking statins and/or ezetimibe, and only 3 compound heterozygous patients (2.14%) underwent liver transplantation owing to significantly high lipid levels.

Molecular analysis

Genetic testing was conducted for all patients. In total, 140 patients with one or two positive variants in LDLR, APOB or PCSK9 were identified. Of these, 75.00% (n = 105) were heterozygous carriers, consisting of 93 individuals with LDLR variants, 11 with APOB variants, and 1 with a PCSK9 variant. The remaining 25.00% (n = 35) were homozygous, including 27 compound heterozygotes, 5 true homozygotes for LDLR, and 3 individuals with double heterozygous variants. Details of these identified homozygous genotypes are provided in Supplementary Table 1.

Additionally, 87 different variants were identified, which are presented in Supplementary Table 2. Figure 1 illustrates the distribution of the identified variants. Specifically, of the 87 distinct variants, 80 were in the LDLR gene, accounting for 91.95%, including 39 missense variants, 11 nonsense variants, 1 synonymous variant, 13 frameshift variants, 13 splice site variants, 1 in-frame deletion, and 2 exon deletions. The APOB and PCSK9 variants accounted for 6.90% (6/87) and 1.15% (1/87), respectively. According to the ACMG and ClinGen classifications, 86.21% (n = 75) of the variants identified were categorized as pathogenic or likely pathogenic, 14.94% (n = 13) were classified as VUS, and 1.15% (n = 1) were classified as likely benign. To analyze the pathogenicity of 13 VUSs and 1 likely benign variant, in silico analysis, in vitro functional studies and family analysis of these variants are shown in Table 2 [19, 20]. Furthermore, the clinical characteristics of patients with VUS or likely benign variants were compared with those of patients with pathogenic or likely pathogenic variants. The analysis found no significant variation in lipid profiles across these groups, as detailed in Supplementary Table 3.

Fig. 1
figure 1

The genotypes of familial hypercholesterolemia (n = 87) identified in the present study. FH: familial hypercholesterolemia; LDLR: low-density lipoprotein receptor; APOB: apolipoprotein B; PCSK9: proprotein convertase subtilisin/Kexin type 9

Table 2 Pathogenicity prediction of VUS and LB variants identified in the cohort with FH

Among the 87 variants, 11 (12.64%), including 6 frameshift variants (54.55%), 2 missense variants (18.18%), 2 exon deletions (18.18%), and 1 nonsense variant (9.09%), had not been previously reported worldwide. The key characteristics of these novel variants are presented in Table 3. In accordance with the ACMG and ClinGen classifications, all novel variants were assessed for pathogenicity, and 81.82% of them (9/11) were categorized as pathogenic or likely pathogenic, whereas 2 missense variants (18.18%) were classified as VUS. The analysis found no significant variation in lipid profiles across patients with novel variants and those with known variants, as shown in Supplementary Table 4. In addition, 16 variants were found in more than one individual, and the 5 most common variants were c.1448G > A (p.W483*, 13.57%), c.1879G > A (p.A627T, 10.00%), c.1747C > T (p.H583Y, 10.00%), and c.1216C > A (p.R406R, 9.29%) of the LDLR gene and c.10579C > T (p.R3527W, 6.43%) of the APOB gene, accounting for 49.29% (69/140) of all patients. The LDLR variants were distributed across 18 exons and 6 introns, with the most frequent variants occurring between exon 3 (10.00%, 8/80) and exon 4 (20.00%, 16/80), which encode the LDLR ligand-binding domain (Fig. 2). The most common APOB variant identified in these patients was c.10579C > T (64.29%, 9/14), which is located in exon 26.

Table 3 Description and function prediction of globally identified novel variants in the cohort with FH
Fig. 2
figure 2

Positions of the variants identified in the LDLR gene. Schematic representation of LDLR exons (exons of different colors encode different functional protein domains) with the relative locations of the detected variants (different shapes represent different kinds of variants)

Genotype‒phenotype correlation

The comparison of the clinical characteristics of HeFH and HoFH patients was made to correlate genotype and phenotype, as presented in Table 4. HoFH patients exhibited a more severe phenotype, with significantly greater lipid profiles levels than HeFH patients did (P < 0.05 for all), except for TG and HDL-C levels. Furthermore, the LDL-C levels of most HeFH patients (63.81%, 67/105) were between 3.6 mmol/L and 4.9 mmol/L, whereas the LDL-C levels of most HoFH patients (60.00%, 21/35) exceeded 13 mmol/L (Fig. 3A). Given the certain degree of overlap in LDL-C levels between the two genotypes, the LDL-C cutoff value for distinguishing HoFH patients from HeFH patients was determined through receiver operating characteristic (ROC) curve analysis (Fig. 3B). The analysis revealed a cutoff value of 10.34 mmol/L, which resulted in a sensitivity of 79.4%, a specificity of 99.0%, and an AUC of 0.893 (P < 0.001).

Table 4 The clinical characteristics of HeFH patients and HoFH patients (n = 140)
Fig. 3
figure 3

Low-density lipoprotein-cholesterol (LDL-C) levels in HeFH patients and HoFH patients. A Frequencies of LDL-C subgroups in HeFH patients and HoFH patients. B Receiver operating characteristic (ROC) curves evaluating the ability of low-density lipoprotein (LDL)-cholesterol values to distinguish between HeFH patients and HoFH patients. HeFH, heterozygous familial hypercholesterolemia; HoFH, homozygous familial hypercholesterolemia; AUC, area under the curve

In addition, individuals with more than one genetic variant causing FH were diagnosed at a younger age (4.00 in HoFH vs. 7.00 in HeFH) and presented a higher incidence of xanthomas, corneal arcus, and increased cIMT (P < 0.05). The primary reason for the initial diagnosis of HeFH was the incidental finding of elevated blood lipids during a routine check-up (88.57%, 93/105), whereas the main reason for the initial diagnosis of HoFH was the presence of disseminated xanthomas (74.29%, 26/35). For lipid-lowering therapy, a low-lipid diet alone was utilized more frequently by HeFH patients compared to HoFH patients (84.76% in HeFH patients vs. 22.85% in HoFH patients, P < 0.001), whereas lipid-lowering medication use was found to be statistically more common in the homozygous group (68.57% vs. 15.23% in HeFH patients, P < 0.001) and liver transplantation (8.57% vs. 0.00% in HeFH patients, P = 0.015) compared to HeFH patients (Table 4). Furthermore, HeFH patients started using lipid-lowering drugs at an older median age compared to HoFH patients (11.71 years for HeFH vs. 6.46 years for HoFH, P < 0.001). Notably, 75.00% of HeFH patients began using lipid-lowering medications after the age of 8, whereas 66.67% of HoFH patients started before the age of 8.

On the basis of the functional changes in LDLR, the variants were classified into "null" variants and "defective" variants. Compared with those with LDLR-defective variants or APOB/PCSK9 variants, heterozygotes with LDLR-null variants presented higher LDL-C levels (5.81 vs. 5.24 vs. 5.80, respectively; P = 0.004) and LDL-C/HDL-C ratios (4.14 vs. 3.96 vs. 2.88, respectively; P = 0.042) (Table 5).

Table 5 The clinical characteristics of HeFH patients with various genotypes (n = 105)

With respect to the homozygous genotype, the 3 patients with double heterozygotes presented a considerably milder phenotype, with markedly lower levels of lipid profiles and APOB than did those with compound heterozygotes and true homozygotes (P < 0.05 for all) (Table 6). Furthermore, the prevalence of xanthomas in double heterozygotes was substantially lower than that in compound heterozygotes and true homozygotes (0% vs. 92.6% vs. 100%, P = 0.002). In terms of carotid artery ultrasound analyses, 60.00% of patients (n = 3) with true homozygotes had increased cIMT, which was greater than the 33.33% of patients (n = 1) with double heterozygotes and the 7.41% of patients (n = 2) with compound heterozygotes (P = 0.018). Moreover, Fig. 4 illustrates the average LDL-C levels in patients with different heterozygous and homozygous FH types.

Table 6 The clinical characteristics of HoFH patients with different genotypes (n = 35)
Fig. 4
figure 4

Low-density lipoprotein-cholesterol levels in patients with different HeFH and HoFH types. ns, not significant; HeFH, heterozygous familial hypercholesterolemia; HoFH, homozygous familial hypercholesterolemia

Finally, the clinical characteristics were compared between HeFH patients carrying the 4 most frequent variants (c.1747C > T, c.1448G > A, c.1216C > A in LDLR, and c.10579C > T in APOB) and those with other variants is presented in Table 7. Although individuals with the c.10579C > T variant presented relatively high concentrations of elevated TC and LDL-C, no statistically meaningful differences were observed (P > 0.05). Moreover, the LDL-C level variability among subjects with the same variant was assessed. As shown in the violin plots in Fig. 5, the c.10579C > T variant exhibited the broadest range of LDL-C values (a maximum-to-minimum variation of 5.10 mmol/L), while the c.1747C > T variant displayed the lowest variability in LDL-C levels (a maximum-to-minimum variation of 2.67 mmol/L).

Table 7 The characteristics of HeFH patients with common variants and other variants (n = 105)
Fig. 5
figure 5

Violin plots reporting the low-density lipoprotein cholesterol (LDL-C) levels observed among patients with the 4 most frequent pathogenic variants. The violin shape represents the smoothed frequency distribution of the LDL-C values expressed in mmol/L. The continuous horizontal line within each value represents the distribution median, whereas the dashed lines represent the first and third quartiles of the value distribution in each group

Discussion

This study details the clinical presentation, biochemical markers and genetic data of 140 pediatric subjects with HeFH and HoFH from multiple centers in China. As far as we are aware, this is the most sizable cohort identified up to the present that outlines the genotype and genotype–phenotype associations in the pediatric population of China.

FH is linked to a lifelong risk of increased cIMT and plaque formation beginning in childhood, leading to the early onset and greater intensity of ASCVD [21,22,23]. In this study, the prevalence of cIMT thickening was 7.14% (n = 10), with 4 of these patients developing carotid plaques. Among these patients with plaques, the youngest was only 4.33 years old, with a plaque at the right carotid bifurcation. Consistent with this study, 10% of the 61 boys and 29 girls aged 10–19 years with FH were found to have carotid plaque in a population-based study [20]. Moreover, reversely cascading screening to identify affected parents could be facilitated by diagnosing children with FH within their first ten years of life, allowing for early detection before the occurrence of their first cardiovascular events [11, 24]. Therefore, early diagnosis and intervention of this disease in childhood are strongly warranted.

In this study, the diagnostic process for patients ranged from two months to seven years, with only 40.71% (57/140) being diagnosed with FH before the age of 5. Unlike in adult patients with FH, classic diagnostic criteria, such as xanthomas, corneal arcus, and premature ASCVD, are rarely seen in pediatric population with FH. Diagnosis in these younger patients mainly depends on elevated LDL-C levels and molecular verification [12]. Consistent with this, the majority of patients (72.14%, 101/140) in the present study visited the outpatient clinic for the first time because of elevated lipid levels discovered incidentally during laboratory investigations. However, further genetic testing was declined by over 20 parents of children whose LDL-C levels fell within the range of 3.6 to 4.9 mmol/L, and 18.09% (19/105) of HeFH patients were identified with LDL-C levels in this range. Moreover, among these patients, only 75.00% (n = 105) were heterozygotes, whereas 25.00% (n = 35) were homozygotes (including compound heterozygotes and double heterozygotes). These findings suggest that a significant number of pediatric HeFH patients may be either missed or diagnosed with delay. Owing to the absence of classic phenotypes in pediatric HeFH patients, most cases remain undiagnosed until midlife or even following the first cardiovascular event, which delays timely intervention [25]. Without timely treatment, lipid levels remain persistently elevated, leading to an ASCVD incidence that is three to four times higher in FH individuals relative to non-FH individuals, with cardiovascular disease (CVD) developing approximately 10 years earlier [26]. Additionally, although the presence of xanthomas served as the initial diagnostic indicator for the majority of HoFH patients (74.29%, 26/35), their average diagnostic timeline was 18.84 months. Furthermore, 5 of the patients were not identified until after undergoing skin biopsies, indicating under-recognition of FH phenotypic indicators by medical professionals and parents. Therefore, there are three recommendations to facilitate the early detection and therapeutic intervention for FH: first, increase awareness of the disease among doctors and parents; second, as advised by the European Atherosclerosis Society (EAS), children between 2 and 10 years should be screened using fasting LDL-C levels, adhering to the clinical diagnostic guidelines for pediatric FH, which include LDL-C concentrations ≥ 3.6 mmol/L, along with signs such as xanthomas, corneal arcus, premature ASCVD, or a familial history of hypercholesterolemia and/or early-onset ASCVD in immediate and extended relatives; and third, conduct genetic screening for individuals meeting the clinical diagnostic criteria [7, 13, 27].

Through genetic testing, 87 different variants were identified among 140 cases, with LDLR variants accounting for 91.95%, APOB variants accounting for 6.90%, and PCSK9 variants accounting for 1.15%, which was consistent with other studies [28]. Notably, 11 variants (12.64%), including 6 frameshift variants, 2 missense variants, 2 exon deletions, and 1 nonsense variant, found in this study have never been reported, suggesting that the FH-causing mutation spectrum continues to expand. Furthermore, frameshift variants caused by the insertion or deletion of one or more bases were the most common novel variants in the present study, unlike previous studies in which missense variants were the most common among novel variants [29, 30]. Since frameshift variants have greater pathogenicity and are more likely to be detected than missense variants, a subset of patients with a mild phenotype, such as those whose LDL-C levels fell within the range of 3.6 to 4.9 mmol/L, may not have been included in the study.

According to the ACMG and ClinGen guidelines, 13 VUS (11 missense variants, 1 splicing variant and 1 in-frame deletion/insertion) and 1 likely benign missense variant were identified in the study. To assess their pathogenicity, in silico analysis tools, such as PolyPhen-2, SIFT, and mutation testers, have been utilized to predict changes in protein structure and function. Additionally, the phenotypes and family histories of patients with VUS or LB variants were analyzed. All patients with these 14 variants exhibited LDL-C concentrations ≥ 3.6 mmol/L, and their immediate or extended family members with the same variants also exhibited hypercholesterolemia. Furthermore, the lipid levels of these patients were similar to those o found in individuals with pathogenic or likely pathogenic variants. However, ex vivo functional analysis and in silico predictions suggested that some of these VUSs and likely benign variants have no adverse effects on LDLR function [31, 32]. Therefore, there is a need for additional insights from laboratory-based functional assays and clinical studies of FH patients with VUS and LB variants to determine their pathogenicity and classification.

Furthermore, 91.25% (n = 73) of the variants of LDLR were located in exons that encode ligand binding domains and EGF precursor homology domains. In particular, the most common variants was in exon 4, which encodes the APOB binding domain, consistent with findings from other studies [27]. In addition, this study demonstrated that the 4 most prevalent LDLR variants were c.1448G > A (13.57%), c.1747C > T (10.00%), c.1879G > A (10.00%) and c.1216C > A (9.29%), accounting for 42.86% of the patients. W483* and H583Y were exclusively observed in Asian populations, and A627T and R406R were not found outside of Chinese individuals [28, 29]. This distribution may be attributed to a founder effect, aligning with previous studies describing FH-related variants in China [33,34,35,36]. Moreover, a hotspot variant of the APOB gene, c.10579C > T, which accounts for 6.43% (9/140) of all the identified variants, has also been reported in other studies from China [29, 33,34,35]. In contrast, the c.10708C > T (p.R3527Q) variant is the most prevalent APOB variant in Caucasian populations [37]. This variant is located in exon 26, encoding an important domain that functions as a ligand for LDLR during receptor-mediated endocytosis. It is associated with relatively high LDL-C and TC concentrations, together with the broadest range of LDL-C values observed in the study. All 5 variants are predominantly found in Asia, especially in China, suggesting their potential importance in Chinese newborn genetic screening for FH [38].

When phenotype severity was correlated with genotype, patients with HoFH clearly presented 2–threefold higher lipid levels [TC, LDL-C, APOB, APOB/APOA, and Lp(a)] than did with HeFH did, in agreement with the current investigation [39]. The LDL-C/HDL-C ratio, which underscores the primary roles of both LDL-C and HDL-C in FH patients, is also greater in HoFH patients than in HeFH patients, indicating greater potential for coronary heart disease [40]. The APOA, which is the primary protein component of HDL particles and a key regulator in lipid metabolism, is much lower in HeFH patients than in HoFH patients [41]. Furthermore, 40.00% (14/35) of HoFH patients exhibited LDL-C levels ≤ 13 mmol/L, despite the EAS consensus statement suggesting diagnostic criteria of LDL-C > 13 mmol/L accompanied by evidence of xanthomas in early childhood (before age 10) [6, 42]. Consequently, an optimal LDL-C cutoff value of 10.34 mmol/L was determined through ROC curve analysis to accurately distinguish HoFH patients from HeFH patients, which corresponds to the LDL-C level of 10 mmol/L observed in other studies [6, 28]. In addition, individuals with multiple FH-causing variants were diagnosed at an earlier age and presented a greater prevalence of xanthomas, corneal arcus, and increased carotid intima–media thickness. Moreover, 75.00% of the patients (3/4) with plaques were HoFH patients, and the youngest patient who developed a plaque at 4.33 years of age was a compound heterozygote for FH. Overall, the genotype of HoFH is associated with a more severe phenotype and a greater likelihood of ASCVD, emphasizing the significance of early diagnosis and intervention [43].

In this study, among the HoFH patients, the mean levels of the main lipid profiles increased in the following order: true LDLR homozygotes > compound LDLR heterozygotes > double heterozygotes, which is consistent with previous research [44]. Interestingly, compared with true homozygotes and compound LDLR heterozygotes, double heterozygotes presented a milder phenotype resembling that of monogenic FH, with a significantly lower lipid profile and a lower incidence of xanthomas. This finding contrasts with previous studies, which could be attributed to a combination of the limited patient cohort and variant heterogeneity [1]. For the different variants, the LDL-C levels, APOB levels, and LDL-C/HDL-C ratios in HeFH patients with null variants were greater than those in HeFH patients with with APOB, PCSK9, or defective LDLR variants, which concurs with prior findings and suggests that more severe LDLR dysfunction is associated with these null variants [45]. Based on the observed genotype–phenotype correlations, the severity of the FH phenotype can be predicted through genetic testing and implementing more aggressive interventions for true LDLR homozygotes, compound LDLR heterozygotes and heterozygotes with null variants owing to their higher lipid levels and increased risk of plaque formation.

Given the significantly elevated risk of early-onset ASCVD, the necessity and critical importance of early intervention cannot be overstated. According to clinical guidelines for managing hypercholesterolemia in pediatric populations, lifestyle and dietary interventions are the first-line treatments for clinically or genetically diagnosed FH patients [9]. For HeFH children aged ≥ 8 years, medication therapy, typically using statins, is recommended if LDL-C concentrations remain ≥ 4.91 mmol/L after 6 months of lifestyle and dietary modifications [46]. Moreover, HoFH children could start lipid-lowering drugs as early as two years of age and consider lipoprotein apheresis or liver transplantation if pharmacotherapy is not effective [42]. In the present study, FH patients were undertreated, with only 15.24% (16/105) of HeFH patients and 68.57% (24/35) of HoFH patients receiving pharmacologic treatment. Additionally, only 3 compound heterozygous patients underwent liver transplantation. More concerningly, among the HoFH patients receiving lipid-lowering therapy, 33.33% (n = 8) initiated treatment after the age of 8, suggesting a significant prevalence of treatment delays. In one respect, since statins, the first-line lipid-lowering drugs, lack pediatric indications in China and ezetimibe is not approved for children under 10 years of age for clinical use, physicians are not sufficiently familiar with the treatment strategies for these medications and are often hesitant to prescribe them. Conversely, parental adherence to LLT in children with FH was suboptimal owing to concerns about potential adverse effects of the medications, the risk of malnutrition from a cholesterol-restricted diet and insufficient awareness of the risks associated with hypercholesterolemia and premature ASCVD. Therefore, additional studies with large cohorts are required to validate the safety and effectiveness of lipid-lowering therapies and to improve early intervention strategies.

Strengths and limitations

This study's strengths are highlighted by the inclusion of a large, diverse sample of pediatric patients with familial hypercholesterolemia from multiple centers across China. Furthermore, all patients underwent comprehensive lipid profile testing and genetic screening, and follow-up data on lipid-lowering treatment regimens were collected. Although this study offers valuable insights into the genotype and genotype–phenotype relationships within the Chinese pediatric population, it is subject to several limitations that must be recognized. First, this study comprises the largest cohort from multiple centers across mainland China to date, the number of patients remains small, particularly for those with HeFH patients. Owing to the milder phenotype in HeFH patients and the reluctance of some parents to pursue further genetic testing, a significant number of cases may have been misdiagnosed or diagnosed with delays. This introduces potential bias in the participant pool and underscores the need for a larger sample size in future study to enhance the representativeness and reliability of the findings. Second, some values for lipid profiles and family history of hypercholesterolemia were recorded on the basis of parents' recall, which may not have been accurate. Third, functional analyses of LDL receptors were not performed on the novel variants identified in this study. Finally, 4 clinically diagnosed probands without detectable variants were identified through whole-exome sequencing. This may suggest the presence of undiscovered disease-causing genes or a polygenic basis for hypercholesterolemia in these patients. Additionally, environmental and lifestyle factors also contribute to clinically defined FH. Therefore, further work should target these patients to identify potentially new causative genes and polygenic susceptibility to elevated plasma LDL-C [47].

Conclusion

In summary, the genotypes and phenotypes of FH in the Chinese pediatric population exhibit significant variability. Additionally, the genetic profile of the Chinese population differs from that of Caucasians, offering a valuable dataset for the clinical genetic screening of FH in China. Furthermore, the findings emphasize the need for earlier diagnosis and treatment of FH in Chinese pediatric patients, as indicated by the older age at diagnosis and treatment in this cohort. To address this, improved early identification through lipid or genetic screening, along with the implementation of timely and regular pharmacological treatments, is crucial to better manage and reduce the burden of FH in this population.

Data availability

No datasets were generated or analysed during the current study.

Abbreviations

ABCG5:

ATP-binding cassette subfamily G member 5

ABCG8:

ATP-binding cassette subfamily G member 8

APOA:

Apolipoprotein A

APOB:

Apolipoprotein B

APOE:

Apolipoprotein E

ASCVD:

Arteriosclerotic cardiovascular disease

BMI:

Body mass index

cIMT:

Carotid intima–media thickness

EAS:

European Atherosclerosis Society

FH:

Familial hypercholesterolemia

HDL-C:

High-density lipoprotein cholesterol

HeFH:

Heterozygous familial hypercholesterolemia

HoFH:

Homozygous familial hypercholesterolemia

LB:

Likely benign

LDL-C:

Low-density lipoprotein cholesterol

LDLR:

Low-density lipoprotein receptor

LDLRAP:

LDLR adaptor protein 1

LLT:

Lipid-lowering therapy

LP:

Likely pathogenic

Lp(a):

Lipoprotein (a)

NGS:

Next-generation sequencing

P:

Pathogenic

PCSK9:

Proprotein convertase subtilisin/Kexin type 9

SDS:

Standard deviation score

STAP1:

Signal-transducing adaptor family member 1

TC:

Total cholesterol

TG:

Triglyceride

VUS:

Variants of uncertain significance

WES:

Whole exome sequencing

References

  1. Sun D, Zhou BY, Li S, et al. Genetic basis of index patients with familial hypercholesterolemia in Chinese population: mutation spectrum and genotype-phenotype correlation. Lipids Health Dis. 2018;17(1):252.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Defesche JC, Gidding SS, Harada-Shiba M, et al. Familial hypercholesterolemia Nat Rev Dis Primers. 2017;3:17093.

    Article  PubMed  Google Scholar 

  3. Abifadel M, Boileau C. Genetic and molecular architecture of familial hypercholesterolemia. J Intern Med. 2023;293(2):144–65.

    Article  CAS  PubMed  Google Scholar 

  4. Fourgeaud M, Lebreton L, Belabbas K, et al. Phenotypic and genotypic characterization of familial hypercholesterolemia in French adult and pediatric populations. J Clin Lipidol. 2022;16(3):298–305.

    Article  PubMed  Google Scholar 

  5. Santos RD, Gidding SS, Hegele RA, et al. Defining severe familial hypercholesterolemia and the implications for clinical management: a consensus statement from the International Atherosclerosis Society Severe Familial Hypercholesterolemia Panel. Lancet Diabetes Endocrinol. 2016;4(10):850–61.

    Article  PubMed  Google Scholar 

  6. Cuchel M, Raal FJ, Hegele RA, et al. 2023 Update on European Atherosclerosis Society Consensus Statement on Homozygous Familial Hypercholesterolemia: new treatments and clinical guidance. Eur Heart J. 2023;44(25):2277–91.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Nordestgaard BG, Chapman MJ, Humphries SE, et al. Familial hypercholesterolemia 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(45):3478–90.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Hu P, Dharmayat KI, Stevens CAT, et al. Prevalence of Familial Hypercholesterolemia Among the General Population and Patients with Atherosclerotic Cardiovascular Disease: A Systematic Review and Meta-Analysis. Circulation. 2020;141(22):1742–59.

    Article  PubMed  Google Scholar 

  9. Cuchel M, Bruckert E, Ginsberg HN, et al. Homozygous familial hypercholesterolemia: new insights and guidance for clinicians to improve detection and clinical management. A position paper from the Consensus Panel on Familial Hypercholesterolemia of the European Atherosclerosis Society. Eur Heart J. 2014;35(32):2146–57.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Sustar U, Kordonouri O, Mlinaric M, et al. Universal screening for familial hypercholesterolemia in 2 populations. Genet Med. 2022;24(10):2103–11.

    Article  CAS  PubMed  Google Scholar 

  11. EAS Familial Hypercholesterolemia Studies Collaboration, Vallejo-Vaz AJ, De Marco M, et al. Overview of the current status of familial hypercholesterolemia care in over 60 countries - The EAS Familial Hypercholesterolemia Studies Collaboration (FHSC). Atherosclerosis. 2018;277:234–55.

    Article  Google Scholar 

  12. European Atherosclerosis Society Familial Hypercholesterolemia Studies Collaboration. Familial hypercholesterolemia in children and adolescents from 48 countries: a cross-sectional study. Lancet. 2024;403(10421):55–66.

    Article  Google Scholar 

  13. Atherosclerosis and Coronary Heart Disease Group of the Chinese Society of Cardiology of Chinese Medical Association; Editorial Board of Chinese Journal of Cardiology. Zhonghua Xin Xue Guan Bing Za Zhi. 2018;46(2):99–103.

  14. Richards S, Aziz N, Bale S, et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med. 2015;17(5):405–24.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Chora JR, Iacocca MA, Tichý L, et al. The Clinical Genome Resource (ClinGen) Familial Hypercholesterolemia Variant Curation Expert Panel consensus guidelines for LDLR variant classification. Genet Med. 2022;24(2):293–306.

    Article  CAS  PubMed  Google Scholar 

  16. Sánchez-Hernández RM, Civeira F, Stef M, et al. Homozygous Familial Hypercholesterolemia in Spain: Prevalence and Phenotype-Genotype Relationship. Circ Cardiovasc Genet. 2016;9(6):504–10.

    Article  PubMed  Google Scholar 

  17. Gu R, Wang H, Wang CL, et al. Gene variants and clinical characteristics of children with sitosterolemia. Lipids Health Dis. 2024;23(1):83.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Tonstad S, Joakimsen O, Stensland-Bugge E, et al. Risk factors related to carotid intima-media thickness and plaque in children with familial hypercholesterolemia and control subjects. Arterioscler Thromb Vasc Biol. 1996;16(8):984–91.

    Article  CAS  PubMed  Google Scholar 

  19. Jiang L, Benito-Vicente A, Tang L, et al. Analysis of LDLR variants from homozygous FH patients carrying multiple mutations in the LDLR gene. Atherosclerosis. 2017;263:163–70.

    Article  CAS  PubMed  Google Scholar 

  20. Etxebarria A, Benito-Vicente A, Stef M, et al. Activity-associated effect of LDL receptor missense variants located in the cysteine-rich repeats. Atherosclerosis. 2015;238(2):304–12.

    Article  CAS  PubMed  Google Scholar 

  21. Minicocci I, Pozzessere S, Prisco C, et al. Analysis of Children and Adolescents with Familial Hypercholesterolemia. J Pediatr. 2017;183:100-107.e3.

    Article  CAS  PubMed  Google Scholar 

  22. Santos RD, Miname MH. Increased subclinical atherosclerosis burden in familial hypercholesterolemia phenotype: What do genetic defects tell us and what are the clinical implications? Atherosclerosis. 2017;263:316–7.

    Article  CAS  PubMed  Google Scholar 

  23. Benn M, Watts GF, Tybjaerg-Hansen A, Nordestgaard BG. Familial hypercholesterolemia in the Danish general population: prevalence, coronary artery disease, and cholesterol-lowering medication. J Clin Endocrinol Metab. 2012;97(11):3956–64.

    Article  CAS  PubMed  Google Scholar 

  24. Berberich AJ, Hegele RA. The complex molecular genetics of familial hypercholesterolemia. Nat Rev Cardiol. 2019;16(1):9–20.

    Article  CAS  PubMed  Google Scholar 

  25. Chen P, Chen X, Zhang S. Current status of familial hypercholesterolemia in China: a need for patient FH registry systems. Atherosclerosis. 2019;10:280.

    Article  Google Scholar 

  26. Huijgen R, Kindt I, Defesche JC, et al. Cardiovascular risk in relation to functionality of sequence variants in the gene coding for the low-density lipoprotein receptor: a study among 29,365 individuals tested for 64 specific low-density lipoprotein-receptor sequence variants. Atherosclerosis. 2012;233(2):2325–30.

    Google Scholar 

  27. Harada-Shiba M, Ohta T, Ohtake A, et al. Guidance for Pediatric Familial Hypercholesterolemia 2017. J Atheroscler Thromb. 2018;25(6):539–53.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Jiang L, Stoekenbroek RM, Zhang F, et al. Homozygous familial hypercholesterolemia in China: Genetic and clinical characteristics from a real-world, multi-center, cohort study. J Clin Lipidol. 2022;16(3):306–14.

    Article  PubMed  Google Scholar 

  29. Jiang L, Sun LY, Dai YF, Yang SW, Zhang F, Wang LY. The distribution and characteristics of LDL receptor mutations in China: A systematic review. Sci Rep. 2015;5:17272.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Leigh S, Futema M, Whittall R, et al. The UCL low-density lipoprotein receptor gene variant database: pathogenicity update. J Med Genet. 2017;54(4):217–23.

    Article  CAS  PubMed  Google Scholar 

  31. Graça R, Alves AC, Zimon M, et al. Functional profiling of LDLR variants: Important evidence for variant classification: Functional profiling of LDLR variants. J Clin Lipidol. 2022;16(4):516–24.

    Article  PubMed  Google Scholar 

  32. Alharbi KK, Kashour TS, Al-Hussaini W, et al. Screening for genetic mutations in LDLR gene with familial hypercholesterolemia patients in the Saudi population. Acta Biochim Pol. 2015;62(3):559–62.

    Article  CAS  PubMed  Google Scholar 

  33. Xiang R, Fan LL, Lin MJ, et al. The genetic spectrum of familial hypercholesterolemia in the central south region of China. Atherosclerosis. 2017;258:84–8.

    Article  CAS  PubMed  Google Scholar 

  34. Jiang L, Sun LY, Pan XD, et al. Characterization of the unique Chinese W483X mutation in the low-density lipoprotein-receptor gene in young patients with homozygous familial hypercholesterolemia. J Clin Lipidol. 2016;10(3):538-546.e5.

    Article  PubMed  Google Scholar 

  35. Jingxin S, Shitong C. Expanding the genetic spectrum for Chinese familial hypercholesterolemia population with six genetic mutations identified using a next-generation sequencing-based laboratory-developed screening test. Mol Genet Genomic Med. 2022;10(12):e2070.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Defesche JC, Schuurman EJ, Klaaijsen LN, et al. Silent exonic mutations in the low-density lipoprotein receptor gene that cause familial hypercholesterolemia by affecting mRNA splicing. Clin Genet. 2008;73(6):573–8.

    Article  CAS  PubMed  Google Scholar 

  37. Rutkowska L, Sałacińska K, Salachna D, et al. Identification of New Genetic Determinants in Pediatric Patients with Familial Hypercholesterolemia Using a Custom NGS Panel. Genes (Basel). 2022;13(6):999.

    Article  CAS  PubMed  Google Scholar 

  38. Kalra S, Chen Z, Deerochanawong C, et al. Familial Hypercholesterolemia in Asia Pacific: A Review of Epidemiology, Diagnosis, and Management in the Region. J Atheroscler Thromb. 2021;28(5):417–34.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Cameron J, Holla OL, Laerdahl JK, et al. Characterization of novel mutations in the catalytic domain of the PCSK9 gene. J Intern Med. 2008;263(4):420–31.

    Article  CAS  PubMed  Google Scholar 

  40. Björnsson E, Thorgeirsson G, Helgadóttir A, et al. Large-Scale Screening for Monogenic and Clinically Defined Familial Hypercholesterolemia in Iceland. Arterioscler Thromb Vasc Biol. 2021;41(10):2616–28.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Carmena-Ramon RF, Ordovas JM, Ascaso JF, et al. Influence of genetic variation at the apo A-I gene locus on lipid levels and response to diet in familial hypercholesterolemia. Atherosclerosis. 1998;139(1):107–13.

    Article  CAS  PubMed  Google Scholar 

  42. Tromp TR, Hartgers ML, Hovingh GK, et al. Worldwide experience of homozygous familial hypercholesterolemia: retrospective cohort study. Lancet. 2022;399(10326):719–28.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Di Taranto MD, de Falco R, Guardamagna O, et al. Lipid profile and genetic status in a familial hypercholesterolemia pediatric population: exploring the LDL/HDL ratio. Clin Chem Lab Med. 2019;57(7):1102–10.

    Article  PubMed  Google Scholar 

  44. Sanna C, Stéphenne X, Revencu N, et al. Homozygous familial hypercholesterolemia in childhood: Genotype-phenotype description, established therapies and perspectives. Atherosclerosis. 2016;247:97–104.

    Article  CAS  PubMed  Google Scholar 

  45. Junyent M, Gilabert R, Jarauta E, et al. Impact of low-density lipoprotein receptor mutational class on carotid atherosclerosis in patients with familial hypercholesterolemia. Atherosclerosis. 2010;208(2):437–41.

    Article  CAS  PubMed  Google Scholar 

  46. Subspecialty Group of Rare Diseases. the Society of Pediatrics, Chinese Medical Association; Subspecialty Group of Cardiology, the Society of Pediatrics, Chinese Medical Association; Subspecialty Group of Child Health Care, the Society of Pediatrics, Chinese Medical Association; Subspecialty Group of Endocrinological, Hereditary and Metabolic Diseases, the Society of Pediatrics, Chinese Medical Association; Editorial Board, Chinese Journal of Pediatrics. Zhonghua Er Ke Za Zhi. 2022;60(7):633–9.

    Google Scholar 

  47. Ramaswami U, Humphries SE, Priestley-Barnham L, et al. Current management of children and young people with heterozygous familial hypercholesterolemia - HEART UK statement of care. Atherosclerosis. 2019;290:1–8.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We are grateful to the patient and their parents for granting us permission to use the data.

Funding

This work is supported by the National Natural Science Foundation of China (81670786) and the Zhejiang Province Medical and Health Leading Talent Project (2024).

Author information

Authors and Affiliations

Authors

Contributions

Zou CC and Fu JF supervised the study. Wang CC, Ma MS, Chi MZ, Zhou Q, Jiang LH, Wang CL, Lu M, Chen XQ, Cheng YY, Ke Q, Wang DY, Qian XX, Ying XM, Zhang JP, Shen QH, Liu LF, Gu R, Zhang ZJ, Feng JH, Wang M, Zhu MQ and Huang K contributed to the data collection and patient management. Huang MN wrote the original draft. All the authors read and approved the final manuscript.

Corresponding authors

Correspondence to Jun-Fen Fu or Chao‑Chun Zou.

Ethics declarations

Ethics approval and consent to participate

The study received approval from the Ethics Committee of the Children’s Hospital of Zhejiang University School of Medicine. Written informed consent was obtained from all participants or their legal guardians prior to the performance of whole exome sequencing (WES).

Competing interests

The authors declare no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Huang, MN., Wang, CC., Ma, MS. et al. Familial hypercholesterolemia in Chinese children and adolescents: a multicenter study. Lipids Health Dis 23, 423 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12944-024-02406-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12944-024-02406-4

Keywords