Potential barriers to reverse cascade screening combined with universal cholesterol screening for paediatric familial hypercholesterolemia: focus on second-degree relatives of a proband

Study population

This single-centre retrospective cohort observational study was conducted at Kagawa University between January 2018 and July 2023. We implemented RCS using genetically confirmed FH as a proband through the “Kagawa health checkups for preventing lifestyle-related diseases in children”^[10]. Data were collected using the electronic medical record system of Kagawa University. Family pedigree was evaluated in second-degree relatives, using a child with a genetic diagnosis of FH as the proband. Relatives suspected of having FH were classified into two groups: those who completed the FH diagnostic process based on the flow chart of the 2022 Japan Atherosclerosis Society (JAS) clinical guidelines and those who did not complete the FH diagnostic process based on these guidelines^[12,13]. Among those who completed the process, cases were further classified into the following four categories based on the 2022 JAS guidelines^[12,13]: “Definite”, “Probable”, “Possible”, or “Unlikely”. These guidelines provide distinct diagnostic algorithms for adults and children, which are shown in Supplementary Figures 1 and 2, respectively. For adults, “Definite” is diagnosed when two or more of the following are present: elevated LDL-C (≥ 180 mg/dL), presence of tendon or cutaneous xanthomas, and a family history of FH or CAD in first-degree relatives. Even if fewer than two criteria are met, a diagnosis of “Probable” can be made when LDL-C is ≥ 250 mg/dL, or when two criteria are met with LDL-C ≥ 160 mg/dL. If only one criterion is met and there is a family history of elevated LDL-C or CAD, the diagnosis is considered “Possible”. Cases not meeting any of these conditions are classified as “Unlikely”. For children, “Definite” is diagnosed when LDL-C is ≥ 140 mg/dL along with a family history of FH or CAD, or when LDL-C is ≥ 180 mg/dL with a relevant family history, or when LDL-C is ≥ 250 mg/dL regardless of family history. Additionally, confirmation of a pathogenic variant of FH also qualifies as “Definite”. “Probable” applies when LDL-C is between 140-179 mg/dL with a family history, or 180-249 mg/dL without such history. “Possible” includes cases with LDL-C 100-139 mg/dL with a relevant family history. Cases with LDL-C < 100 mg/dL despite a family history, or < 140 mg/dL with no family history, are considered “Unlikely”. Those who did not complete the FH diagnostic process were classified into the following five categories: “Untested lipids in children”, “Bereavement”, “CAD with unspecified details”, “Dyslipidaemia with unspecified LDL-C levels”, and “No information on CAD or dyslipidaemia”. Specifically, the category “Untested lipids in children” includes cases in which blood testing could not be performed due to fear of needles or lack of parental consent, both of which are often influenced by the child’s age. “Bereavement” refers to cases, particularly involving grandparents, where family history could not be obtained due to the death of the relative. “Unspecified LDL-C levels” include cases where blood was drawn, but LDL-C values were not recorded in the medical records. “Unspecified CAD history” refers to cases where the presence or absence of coronary artery disease could not be confirmed through medical records or patient reports. Finally, “No information available” describes cases where no relevant medical information could be obtained at all, making risk evaluation impossible. In this study, the family history recorded during the explanation of genetic test results was defined as the initial visit. After that, patients received ongoing treatment, primarily lipid-lowering therapy, provided by local primary care physicians, while annual follow-up visits were conducted at our institution. At each follow-up, we reviewed and updated the family history. If new at-risk relatives were identified, further evaluation was performed. During the initial visit, both parents were interviewed and tested for LDL-C to assess the likelihood of FH. If one parent was suspected of having FH, we investigated second-degree relatives on that side of the family according to the 2022 JAS clinical guidelines. If both parents were suspected, both family lines were investigated.

Effectiveness and barriers assessment

To obtain a clear demonstration and understanding of how patients were distributed among those diagnosed with FH, effectiveness was evaluated by categorising patients who completed the FH diagnostic process based on the flowchart of the 2022 JAS clinical guidelines. In contrast, barriers were evaluated based on the reasons provided for incomplete diagnostic processes, including challenges such as “Untested lipids in children”, “Bereavement”, “CAD with unspecified details”, “Dyslipidaemia with unspecified LDL-C levels”, and “No information on CAD or dyslipidaemia”. We also evaluated the number of new FH diagnoses or reasons for incomplete diagnosis within second-degree relatives and documented the overall progression of the diagnostic process.

Genetic analysis

All children underwent genetic analysis at Kanazawa University, where their genotypes were examined using a next-generation sequencing platform^[14]. The coding regions of LDLR (NM_000527.5), APOB (NM_000384.3), PCSK9 (NM_174936.4), and LDLRAP1 (NM_015627.3) were sequenced, following the established protocols. Additionally, copy number variations at the LDLR locus were assessed using the eXome Hidden Markov Model^[15]. Adhering to the guidelines of the American College of Medical Genetics and Genomics, the pathogenic variant of FH was determined during multidisciplinary meetings involving specialists in genetics.

Ethical considerations

This study was approved by the Ethics Committee of Kagawa University (H30-059). All procedures adhered to the ethical standards set by the Institutional and National Human Research Committees and conformed to the Declaration of Helsinki (1975, revised in 2008). Written informed consent for the genetic testing of the children was obtained from at least one parent.

Statistical analysis

Patients who completed the FH diagnostic process were classified into four categories-“Definite”, “Probable”, “Possible”, or “Unlikely”-according to the 2022 JAS clinical guidelines. Those who did not complete the FH diagnostic process were classified into five categories: “Untested lipids in children”, “Bereavement”, “CAD with unspecified details”, “Dyslipidaemia with unspecified LDL-C levels”, and “No information on CAD or dyslipidaemia”. Using these categories, we evaluated the effectiveness and barriers of RCS in the diagnostic process. To evaluate whether the distribution between first-degree and second-degree relatives differed significantly within each diagnostic group, each group was compared with all other groups combined using the chi-squared test. Fisher’s exact test was used when > 20% of the expected cell frequencies were less than five. Statistical analyses were conducted using IBM SPSS Statistics version 29 (IBM Corp., Armonk, NY, USA), with the significance level set at P < 0.05.

The effectiveness of reverse cascade screening

This study diagnosed 49 patients from 48 families with FH. The number of diagnosed cases per index patient was 1.02, which is comparable to the range reported in previous studies (mean 1.65, range 0.22-8.0)^[16]. We found that RCS, including genetic testing, can lead to the diagnosis of FH in relatives. Given that FH is an autosomal dominant genetic disorder, it can be diagnosed in at least one parent. Therefore, this approach can facilitate the diagnosis of FH not only in children but also in their parents^[17]. Thus, RCS has the potential to identify patients with FH who have not yet been diagnosed and are asymptomatic. FH is an autosomal dominant disorder, and when a child is genetically diagnosed with FH, it is highly likely that one of the parents also has FH. Furthermore, family members are also likely to be affected. Therefore, the diagnosis of FH in these relatives should not be considered of limited significance, but rather as an important finding that indicates the broader presence of FH within the family. Since second-degree relatives also include the first-degree relatives of the proband’s parent, we believe that not only cascade screening for first-degree relatives but also the continuous updating of family history across all blood relatives is essential for improving FH detection. Regarding cost-effectiveness, we have previously evaluated the economic impact of this screening approach using a simulation model, which demonstrated its potential utility in clinical practice^[18].

Moreover, this study demonstrated the importance of family-based follow-up, which includes regularly updating family histories^[19]. This implementation identified 13 additional FH diagnoses after the initial diagnosis of 36 cases. Importantly, regularly updating the family histories of children diagnosed with FH could improve their adherence to treatment, introduce essential lifestyle changes, and lead to the diagnosis of new FH cases.

Barriers to reverse cascade screening

The number of patients diagnosed with FH was lower among second-degree relatives than among first-degree relatives (47 cases in first-degree relatives and 2 cases in second-degree relatives). Conversely, the number of suspected FH cases for which the screening flowchart could not be completed was higher among second-degree relatives than among first-degree relatives (25 cases in first-degree relatives and 133 cases in second-degree relatives). This discrepancy may be due to the absence of the second-degree relative during the medical consultation, leading to “CAD with unspecified details”, “Dyslipidaemia with unspecified LDL-C levels”, and “No information on CAD or dyslipidaemia” among second-degree relatives. When constructing family information, documenting negative findings is crucial because “No information on CAD or dyslipidaemia” may suggest a lack of clarity regarding whether the relevant data were collected. Thus, documenting negative findings ensures the accuracy of the clinical records and aids in more effective risk assessment and management. Additionally, the lack of information on CAD or dyslipidaemia is a significant issue that can be addressed by raising awareness regarding FH among healthcare professionals through educational initiatives. This is important as the early detection and treatment of FH depend significantly on healthcare professionals. Given that the rate of diagnosis of FH is reported to be below 10% in Asian populations, increasing awareness may lead to more frequent medical consultations and, consequently, higher rates of diagnosis^[20]. In addition, raising awareness among the public is crucial for addressing issues such as “CAD with unspecified details” or “Dyslipidaemia with unspecified LDL-C levels”, and it is therefore important to foster interest regarding FH among the public and encourage families to take a proactive approach to FH diagnosis. In fact, public education campaigns have been shown to significantly increase awareness and engagement in FH screening programmes, which could improve the early diagnosis and management of FH^[21].

The category “Untested lipids in children” also represented a barrier to FH diagnosis. In children who are unable to undergo lipid testing due to fear of needles or lack of parental consent, non-invasive genetic testing using a buccal swab may be a helpful alternative. Previous studies have reported its successful use in paediatric FH screening and its potential to improve cascade testing uptake^[22]. To minimize the barrier posed by invasive procedures, the development of non-invasive testing methods, including buccal swab-based genetic testing, is warranted.

The results of this study also demonstrated that family-based follow-up could reduce “No information on CAD or dyslipidaemia” and improve the diagnosis of FH. Previous studies suggest that direct contact or home visits to families of probands can significantly enhance the diagnosis of FH^[20]. However, these methods are limited as healthcare providers are not always able to make direct contact (calls or letters from the FH service) or other contact (all alternative methods besides direct or indirect contact with adults) with these individuals, which may result in patient-centred approaches failing to encourage relatives to seek medical evaluation. Therefore, utilising Information and Communication Technology (ICT) instead of other contact methods might address the issue of an incomplete FH diagnostic process^[23]. The use of ICT, such as electronic health records and machine learning algorithms, to efficiently identify potential FH cases has shown promise, with several studies reporting the effectiveness of such approaches^[24-26]”. To address the missing information observed in this study, integrating electronic health record systems and using standardized questionnaires may help improve data quality and reduce information gaps. In Kagawa Prefecture, the “K-MIX R” regional health information network connects all medical institutions via electronic health records. Through this network, the results of universal screening are shared to enhance the diagnostic accuracy of FH and optimise family-based treatment. This initiative employs an opt-in system that enables data sharing based on patient consent, ensuring privacy protection and addressing ethical considerations. Currently, information from other hospitals is gathered through written communication, which can be inefficient and delay the diagnostic process. If healthcare facilities were connected through an integrated network, it would enable easier and more timely access to the detailed data necessary for FH diagnoses, such as accurate LDL-C levels and CAD events. Such a network could significantly enhance diagnostic efficiency and improve the coordination between medical institutions. Furthermore, utilising ICT to create an interconnected health information system would facilitate the sharing of necessary diagnostic data and streamline the overall screening process, potentially increasing FH diagnosis rates.

Limitations

This study was based on data from a single medical institution in Japan, which may limit the generalisability of the findings. Differences in cultural factors, such as family health information sharing willingness, socioeconomic factors, cultural contexts, and healthcare infrastructure, may also affect the applicability of our results to other regions in Japan and international settings. These factors may be potential reasons for the low diagnosis rate of second-degree relatives. Therefore, targeted measures such as community-based health education or economic incentives might improve awareness and participation. Future studies involving multicenter data are warranted to verify our conclusions' broader relevance and applicability. Part of the family history and medical history was obtained through self-reports by patients or their family members, which may have introduced recall bias and information bias related to self-reported data. Annual in-person follow-up visits were conducted to update family histories; however, alternative methods such as telephone calls, home visits, or electronic platforms were not utilised. Since previous studies have reported improved FH diagnosis rates through telephone or home visit strategies, integrating these approaches warrants consideration in future implementation^[27]. This study is a limited use of genetic testing in relatives of FH probands with a known pathogenic variant of FH. In Japan, predictive genetic testing for asymptomatic individuals is not generally recommended in the guidelines^[12]. Therefore, we focused on relatives with clear clinical indicators. Moving forward, there is a need to promote appropriate and ethical use of genetic testing. A key limitation of this study is its focus on the diagnostic stage, without evaluating post-diagnosis intervention effects such as medication adherence or reduction in cardiovascular events. We acknowledge the importance of long-term follow-up data and recommend that future research, in collaboration with academic societies and government agencies, incorporate clinical outcome indicators to comprehensively assess the value of screening programmes, including treatment effectiveness, patient adherence, and clinical endpoints.

Conclusions

This study demonstrated that RCS combined with UCS for paediatric FH, utilising genetic testing, is effective for the early diagnosis of FH in asymptomatic cases. However, barriers such as difficulties in approaching second-degree relatives hinder the diagnosis of FH in their families. To overcome these barriers, family-based follow-ups, increased awareness, and an efficient system for the accurate and accessible collection of family medical information are crucial.