Same disease, different testing approaches: global survey highlights the need for standardized FH genetic testing

Familial hypercholesterolemia (FH) is a common inherited disorder affecting approximately 1 in 250 individuals and is caused by pathogenic variants in the LDLR, APOB, or PCSK9 genes. It is characterized by persistently elevated low-density lipoprotein cholesterol (LDL-C) levels and a markedly increased risk of premature atherosclerotic cardiovascular disease (ASCVD).^1,2 This risk can be substantially reduced with LDL-C–lowering therapies when treatment is initiated early, making timely diagnosis essential.^3,4 Yet despite increasing awareness and advances in genetic testing, approximately 90% of FH cases worldwide remain undiagnosed. ⁵

Why genetic testing matters in FH

While clinical criteria can identify suspected FH, a definitive diagnosis requires genetic testing, which improves diagnostic accuracy, enables cascade screening, and supports personalized treatment. ^4,6

As FH screening programs expand globally and more treatments are being available, genetic testing has become an increasingly important component of patient care. However, important questions remain regarding how FH testing is performed in different countries and healthcare systems. Are the same referral criteria being used for testing? Are laboratories using similar methodologies? Are the same genes being analyzed? Understanding these differences is essential for improving and standardizing FH diagnosis guidelines worldwide. ^4,7

A global survey of FH genetic testing practices

To address these questions, researchers conducted an international survey of centers participating in the global Familial Hypercholesterolemia Studies Collaboration (FHSC) registry across 55 countries. The survey examined referral criteria, testing methodologies, gene coverage, and variant interpretation practices.⁸

The findings provide the most comprehensive global overview of FH testing practices to date and reveal substantial variation between countries and centers. These differences may influence who gets tested, which variants are detected, and the accuracy and consistency of FH diagnosis, while highlighting opportunities to improve the standardization of FH testing worldwide.

Key insights from the survey

Different criteria are used to select patients for testing

Most centers relied on established clinical criteria to determine when FH genetic testing should be performed. The Dutch Lipid Clinic Network (DLCN) criteria were the most widely used in both adults and children, although some centers combined DLCN with other frameworks, such as Simon–Broome and Make Early Diagnosis to Prevent Early Death (MEDPED). Referral thresholds also varied across centers. Besides established scoring systems, some laboratories considered individual clinical features such as elevated LDL-C levels, family history, premature cardiovascular disease, and cutaneous signs alongside these criteria. In some cases, centers relied solely on these features to determine eligibility for genetic testing.

Although referral practices were broadly similar across countries, Simon–Broome and MEDPED were primarily used in high-income countries, some of which had implemented routine government-supported FH genetic testing programs. ⁹ These findings highlight that no single diagnostic framework is optimal for all populations and healthcare settings. ¹⁰ Broader criteria may improve case detection but increase testing demand, whereas stricter criteria may miss affected individuals. The widespread use of DLCN in children is particularly noteworthy, as it was not developed or validated for pediatric populations and may fail to identify a substantial proportion of affected children. ^11,12,13,14

Testing methodologies and gene coverage vary widely

Most centers used blood samples for DNA extraction, with next-generation sequencing (NGS) gene panels being the most common testing method for index cases. However, testing approaches varied considerably, ranging from comprehensive NGS panels to exome sequencing, genome sequencing, Sanger sequencing, and targeted testing of country-specific variants. Gene coverage also differed across laboratories. While most centers screened the three primary FH genes (LDLR, APOB, and PCSK9), fewer than half included the recommended FH-associated and phenocopy genes. ⁴ Some centers also continued to include STAP1 despite evidence that it is not a causative gene for FH. ^15,16 These differences may affect diagnostic yield and contribute to missed diagnoses and inconsistent clinical outcomes. The findings also reflect a broader shift toward more comprehensive and standardized genetic testing, prompting manufacturers to expand their solutions in line with evolving recommendations. 

Opportunities to improve cascade screening and CNV detection

For relatives of index cases, targeted testing of the known familial variant using Sanger sequencing or Multiplex Ligation-dependent Probe Amplification (MLPA) is generally considered the most cost-effective approach. Nevertheless, some centers continued to use broader NGS-based testing, while others did not test relatives at all.

The survey also revealed important gaps in copy-number variant (CNV) detection. Because CNVs account for a significant proportion of LDLR variants and are often detectable from existing NGS data,¹⁷ routine CNV analysis could improve diagnostic yield and reduce false-negative results at minimal additional cost, particularly in large-scale FH screening and cascade screening programs.

Polygenic risk assessment remains inconsistent

Only one-third of surveyed centers reported testing for polygenic hypercholesterolemia, and most performed such testing only when no monogenic FH-causing variant was identified. While polygenic risk is increasingly recognized as a contributor to elevated LDL-C levels, its clinical utility remains uncertain. The wide variation in scoring methods, together with limited validation in children, highlights the need for clearer guidance before polygenic testing can become part of routine FH diagnostics.  

Variant classification and interpretation require standardization

Nearly all centers performed variant pathogenicity assessment, most commonly using American College of Medical Genetics and Genomics (ACMG) guidelines, often supported by databases, computational tools, and other sources of evidence. Because variant interpretation directly influences diagnosis, cascade screening, and clinical decision-making, standardized and evidence-based classification practices are essential. The findings support prioritizing gene-specific guidelines and expert-reviewed classifications over general ACMG criteria whenever available.  

 

Moving toward standardized FH testing

The survey demonstrates that FH genetic testing remains highly heterogeneous worldwide, with differences in referral criteria, testing methodologies, gene coverage, CNV detection, and variant interpretation that may affect diagnostic yield and patient care.

To address these challenges, the FHSC Genetics Working Group recommends greater standardization of FH genetic testing through broad gene coverage, reliable CNV detection, standardized variant interpretation, and consistent reporting practices. These measures can improve diagnostic accuracy, facilitate earlier identification of affected individuals and their relatives, and help optimize patient management, while allowing flexibility for local healthcare needs and resources.

As laboratories work toward greater standardization of FH genetic testing, the need for comprehensive, IVDR-compliant solutions continues to grow. To support this evolution, Devyser is developing an updated IVDR-certified FH solution, planned for launch in 2027, designed to align with emerging best-practice recommendations. The new solution will include the eight genes recommended by the FHSC Genetics Working Group (LDLR, APOB, PCSK9, APOE, LDLRAP1, LIPA, ABCG5, and ABCG8) together with integrated software, automated polygenic FH calculations, analysis of clinically relevant statin-response variants and two key Lp(a)-associated SNPs, all within a streamlined NGS workflow. Together, these enhancements are intended to help laboratories implement more comprehensive and standardized FH genetic testing workflows.

References

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