Abstract
Objectives
The Rare Disease Diagnostic Support Program in the Republic of Korea aims to improve early diagnosis and diagnostic yield for patients with rare diseases, particularly for those residing in non-metropolitan areas, by providing whole genome sequencing (WGS) services through regional medical institutions. This study evaluated the performance of the program, focusing on its clinical utility, including early diagnosis and treatment linkage, and its policy impact related to patient benefits.
Methods
From August 2024, WGS was performed on 410 patients with suspected rare diseases at 23 institutions outside the metropolitan area. A one-stop diagnostic pathway was established to perform sample collection, test referral, report delivery, and genetic counseling within a single clinical flow based on the patient’s location of residence. Sequencing was performed by external laboratories.
Results
Among the 410 patients, pathogenic variants were identified in 129 (31.5%), with a turnaround time of 28 days. Of those diagnosed, 78.2% received treatment benefits via national programs such as co-payment exemption and medical expense support programs. Approximately 30% of the patients were eligible for therapeutic intervention, particularly medication or dietary therapy. Family genetic testing of three members identified potential carriers or high-risk groups in 28 households (65.1%). Consent for secondary findings was 99.0%, with clinically significant variants found in 3.9% of cases.
Conclusions
The program demonstrated clinical value by improving diagnostic accessibility, reducing regional disparities, facilitating timely treatment, and supporting preventive care through family risk identification. These findings support the need for sustainable expansion of genome-based diagnostic services in the national health policy.
Keywords: Rare disease, Whole genome sequencing, Diagnosis, Treatment
Key messages
① What is known previously?
In the Republic of Korea, the diagnostic infrastructure for rare diseases is primarily concentrated in metropolitan areas, resulting in chronic diagnostic delays and limited access to diagnostic services for patients in non-metropolitan regions.
② What new information is presented?
The Rare Disease Diagnostic Support Program in the Republic of Korea has improved diagnostic accessibility by supporting genetic testing for rare diseases at specialized regional centers and tertiary hospitals.
③ What are the implications?
This program suggests that strengthening community-based diagnostic support systems can facilitate earlier diagnosis, reduce regional disparities in rare disease care, and enhance the effectiveness of national rare disease management systems.
Introduction
Currently, more than 7,000 rare diseases have been reported, and approximately 80% of these are caused by genetic factors [1,2]. Approximately 75% of rare diseases manifest in infancy, and 30% are associated with premature death. Therefore, early diagnosis and prompt treatment are crucial for patient prognosis [1,3]. The diagnosis of rare diseases, however, is difficult owing to their rarity, and in some cases, conventional diagnostic methods may fail to identify them. Therefore, patients often have to visit multiple healthcare facilities to obtain a diagnosis, resulting in a phenomenon known as the “diagnostic journey” [4]. The mean diagnostic delay in cases of rare diseases is approximately 7 years, with a considerable proportion of patients remaining undiagnosed for more than a decade [5-7].
Therefore, to resolve structural problems in the diagnosis of rare diseases, the Korea Disease Control and Prevention Agency (KDCA) introduced the “Outreach Support Program for the Diagnosis of Rare Diseases.” This program provides support to patients with rare diseases by enabling them to visit a rare disease center or advanced general hospital in their area without having to travel long distances, where they can receive an early diagnosis and test interpretations through genetic diagnosis services utilizing whole genome sequencing (WGS). The aim of this program is to enhance geographical access to healthcare for patients while introducing precision genomic testing technologies such as WGS to increase the diagnosis rate for rare diseases that are difficult to diagnose using conventional methods [8-10]. Furthermore, this program is intended to provide more than just diagnostic support and seeks to connect patients with timely treatment through early diagnosis, management of high-risk groups by screening potential patients and carriers based on family-based genetic testing, and effective implementation of preventive healthcare for rare diseases.
To address the management of high-risk groups, this program also reports on “secondary findings (SF),” gene variants discovered in the analyzed genome that are unrelated to the original diagnostic purpose. Any SF is reported in accordance with the recommended criteria presented by the American College of Medical Genetics and Genomics (ACMG) and is currently based on the ACMG SF v3.2 list, targeting 81 genes with pathogenic variants that enable early intervention for cardiovascular disease, cancer, metabolic disorders, and other conditions [11]. SFs play a pivotal role in disease prevention and health management, offering invaluable insights not only to patients but also to their families, which underscores their significance in precision medicine and public health.
Recent studies have indicated the potential for genome-based diagnostics to facilitate the development of personalized therapies, with reports indicating that personalized treatment strategies can be applied to approximately 10% of patients with rare diseases [3]. Consequently, this program holds significant institutional value owing to its introduction of precision genetic diagnosis technology centered on WGS, facilitating more precise diagnosis and treatment of rare diseases. This report aims to identify and examine the effectiveness and validity of diagnosis and treatment coordination through the program, based on the results of the 2024 Outreach Support Program for the Diagnosis of Rare Diseases.
Methods
In August 2024, the KDCA-supported Outreach Support Program for the Diagnosis of Rare Diseases initiated a nationwide selection process, identifying a total of 410 patients suspected of having rare diseases from 23 rare disease centers and tertiary hospitals situated beyond the Seoul metropolitan area (hereinafter referred to as participating healthcare institutions). Samples were collected and subsequently subjected to WGS at external testing institutions, in accordance with the following procedures.
1. Selection of Participants and Sample Collection
Among patients who visited participating healthcare institutions in their area of residence and were suspected of having a rare disease, only those who provided written consent on the genetic testing consent form, human biological material donation consent form, and SF consent form after consultation with healthcare providers were enrolled in the program. The samples used were peripheral blood, dried blood spot cards, and tissue DNA. The collected samples were sent to designated external testing institutions.
2. Whole Genome Sequencing
The collected samples were then subjected to WGS using the NovaSeq X Plus (Illumina) platform with a 150-base pair paired-end approach at external specialized testing institutions [12].
3. Generation and Provision of Diagnostic Reports and Follow-up Testing Support
The diagnostic reports were generated by a diagnostic report generation committee comprising three clinical geneticists, one diagnostic laboratory specialist, and one bioinformatics specialist from Pusan National University Yangsan Hospital and external testing institutions. The results were subsequently uploaded to the Integrated Disease Control System of the KDCA, where they were made available as diagnostic reports for healthcare providers and patients. The uploaded diagnostic reports for healthcare providers and patients were then forwarded to the referring doctors, who subsequently provided the diagnostic reports to patients and their guardians during consultations. The diagnostic reports for patients included additional explanations of terms to facilitate comprehension of the results and methods for interpreting variant information. This facilitates patient and family understanding of diagnostic reports, enabling effective communication with healthcare providers regarding future treatment and management plans.
The additional follow-up tests provided after WGS were as follows: 1) verification of causative gene variants by methods including Sanger sequencing, gap-polymerase chain reaction, and RNA testing; and 2) screening for high-risk groups by supporting genetic testing for parents and siblings (up to three people).
4. Report on SFs
In conjunction with WGS, SF analysis was conducted on 81 genes with an elevated disease risk, as delineated by the ACMG recommendations (2023, v3.2) [11]. This analysis was restricted to individuals who had previously provided consent (n=406).
Results
1. Age Distribution of Individuals Tested by WGS
Among the 410 patients with rare diseases who were tested by WGS, pediatric patients under the age of 12 years accounted for the highest percentage (n=235, 57.3%), followed by adolescents aged 12–18 years (n=85, 20.7%) and adults aged 18 years and older (n=90, 22.0%).
2. Status of Overall Diagnosis and Diagnosis Rates by Age for Genetic Testing
Pathogenic gene variants were identified in 129 (31.5%) participants, with the highest frequency noted in the pediatric age group (under 12 years of age), accounting for 80.6% (104/129) of all positive cases. The diagnostic rates for adolescents and adults were determined to be 15.5% (20/129) and 3.9% (5/129), respectively.
3. Time Required for WGS
The mean interval from specimen collection from patients suspected of having rare diseases to the delivery of the final diagnostic report was approximately 28 days.
4. Effectiveness of Rare Disease Treatment Coordination and Socioeconomic Support
Among the 129 patients diagnosed with rare genetic diseases, 39 (30.2%) were confirmed to have diseases for which clinical treatment strategies were available, such as therapeutic drugs (15), targeted diets (18), and surgical interventions (6) (Table 1). The capacity for these patients to receive early treatment upon diagnosis indicates the potential for proactive intervention and more efficient disease management for high-risk groups with rare diseases. Furthermore, 78.2% (101/129) of patients with a confirmed diagnosis were referred to national support programs, such as the National Health Insurance Service’s special assessment system or healthcare expense support program for patients with rare diseases. These patients received various forms of social and economic support, including assistive devices and special diets, to reduce their healthcare expenses.
Table 1. Current therapeutic approaches by rare disease category.
| No. | Disease group | Disease name | Clinical therapeutic strategy |
|---|---|---|---|
| 1 | Endocrine, nutritional, and metabolic diseases | Glycogen storage disease 1b type A | Cornstarch, antibiotics, G-CSF |
| Propionic acidemia | Metronidazole antibiotics, sodium benzoate, biotin supplementation, dietary therapy (low-protein diet) | ||
| 2 | Congenital malformations, deformations, and chromosomal abnormalities | Achondroplasia | Growth hormone, surgical treatment |
| Angelman syndrome | Methylphenidate, ketogenic diet, antiepileptic drugs | ||
| CHARGE syndrome | Surgical correction (tracheostomy, heart defects, cleft lip), hormone replacement therapy, hearing aids, cochlear implant | ||
| Hypoplastic left heart syndrome |
PGE-1 injection, surgery, heart transplantation | ||
| Neurofibromatosis (nonmalignant) type 1 | Koselugo (selumetinib) oral medication | ||
| Noonan syndrome | Growth hormone: norditropin | ||
| 3 | Circulatory system diseases | Moyamoya disease | Antiepileptic drugs, surgical treatment (extracranial-intracranial bypass) |
| 4 | Nervous system diseases | Hereditary spastic paraplegia | Muscle relaxants: baclofen, tizanidine, dantrolene, diazepam, clonazepam |
| MELAS syndrome | Coenzyme Q, L-arginine, levocarnitine | ||
| PKD | Antiepileptic drugs: phenytoin, carbamazepine | ||
| 5 | Disorders of blood, hematopoietic organs, and immune mechanisms | Blackfan-Diamond syndrome | Adrenal corticosteroids, bone marrow transplantation |
| Fanconi’s anaemia | Steroids, androgens, hematopoietic stem cell transplantation | ||
| Wiskott–Aldrich syndrome | Hematopoietic stem cell transplantation, splenectomy, immunoglobulin and gamma globulin administration, aspirin | ||
| 6 | Uncoded | Brain-lung-thyroid syndrome | Thyroid hormone administration, tetrabenazine, levodopa |
| Congenital disorder of glycosylation | Mannose supplementation, liver transplantation | ||
| Diffuse pulmonary lymphangiomatosis | Surgical removal, pharmacological therapy (interferon-alpha, steroids), radiation therapy | ||
| Dravet syndrome | Antiepileptic drug therapy, ketogenic diet, CBD treatment | ||
| Familial hypercholesterolemia homozygote | HMG-CoA reductase inhibitors, bile acid sequestrants, PCSK9 inhibitors | ||
| Hereditary chronic pancreatitis | Fluid therapy for recurrent acute pancreatitis, pain control, nutritional support, pancreatic enzyme replacement, necrosectomy, drainage, decompression, pancreatectomy | ||
| HNRNPU-related disorder | Antiepileptic drugs, sodium valproate | ||
| HDR syndrome | Oral calcium supplements, hearing aids, cochlear implantation | ||
| OPHN1-related disorder | Fasudil | ||
| RANBP2 related acute encephalopathy | High-dose steroids, IVIG, other immunosuppressants |
PKD=paroxysmal kinesigenic dyskinesia; HDR=hypoparathyroidism-sensorineural deafness-renal disease; G-CSF=granulocyte colony-stimulating factor; PGE-1=prostaglandin E1; CBD=cannabidiol; IVIG=intravenous immunoglobulin.
5. Expansion of the Management System after Rare Disease Diagnoses
In family genetic counseling conducted for patients diagnosed with rare diseases, 33.3% (43/129) consented to primary genetic testing, and among them, 28 households (65.1%) were identified as potential carriers or high-risk groups before symptom manifestation, underscoring the necessity for preventive management approaches for rare diseases.
6. SF Analysis Results
In this study, 99.0% of the 410 patients suspected of having a rare disease consented to the provision of SF information in accordance with the ACMG v3.2 guidelines. Participants who consented to participate underwent additional genetic testing for disease-causing or clinically significant variants identified through genome sequencing. These variants were also verified by Sanger sequencing. The analysis revealed clinically significant genetic variants associated with high risk in 3.9% of the 406 participants who provided consent. A considerable proportion of these variants have been associated with disease groups that necessitate prompt intervention and prevention measures, including cardiovascular disease and hereditary cancer (Table 2).
Table 2. Categories of symptoms and secondary findings by disease based on whole genome sequencing requests.
| Symptom category | Disease name | Disease classification | SF gene | Number of cases |
|---|---|---|---|---|
| Dermatological disorders | Arrhythmogenic right ventricular dysplasia type 10 | Cardiovascular | DSG 2 | 1 |
| Endocrine disorders | Familial hypertrophic cardiomyopathy type 1 | Cardiovascular | MYH 7 | 1 |
| Familial hypercholesterolemia type 3 | Cardiovascular | PCSK 9 | 1 | |
| Neurodevelopmental disorder | Hereditary breast and ovarian cancer syndrome type 1 | Cancer | BRCA 1 | 1 |
| Lynch syndrome type 4 | Cancer | PMS 2 | 1 | |
| Dilated cardiomyopathy type 1D | Cardiovascular | TNNT 2 | 1 | |
| Dilated cardiomyopathy type 1G | Cardiovascular | TTN | 4 | |
| Neurology disorder | Familial hypertrophic cardiomyopathy type 4 | Cardiovascular | MYBPC 3 | 3 |
| Loeys-Dietz syndrome type 2 | Cardiovascular | TGFBR 2 | 1 | |
| Tumor syndrome | Lynch syndrome type 5 | Cancer | MSH 6 | 2 |
SF=secondary findings.
7. Status of the Diagnostic Journey Period
Among the 410 participants who participated in this program, 107 patients with positive variants and clearly identified symptom onset dates were analyzed, yielding an average diagnosis period of 7.4 years. A detailed examination of the duration until diagnosis revealed that 21 patients (19.6%) were diagnosed within less than 1 year after symptom onset, 35 (32.7%) were diagnosed within 1–5 years, 24 (22.4%) were diagnosed within 6–10 years, and 27 (25.2%) were diagnosed after 10 years (Table 3).
Table 3. Distribution of time required for diagnosis (determination of rare genetic disease).
| Total | Period (yr) | |||||||
|---|---|---|---|---|---|---|---|---|
| <1 | 1–5 | 6–10 | 11–15 | 16–20 | 21–25 | 26–30 | ≥31 | |
| 107 (100) | 21 (19.6) | 35 (32.7) | 24 (22.4) | 10 (9.3) | 6 (5.6) | 8 (7.5) | 0 (0.0) | 3 (2.8) |
Unit: n (%).
Discussion
The Outreach Support Program for the Diagnosis of Rare Diseases was launched as a core initiative to strengthen support for patients with rare diseases and their families and establish an effective rare disease management system, in accordance with the strategic objectives of the Second Comprehensive Rare Disease Management Plan (2022–2026). This study aimed to empirically validate the efficacy of a one-stop rare disease diagnosis support service that utilizes highly efficient WGS for patients and their families living outside of the Seoul metropolitan area, thereby demonstrating that such a service is feasible in local medical settings.
Because of WGS-based genetic testing conducted for a total of 410 patients suspected of having rare diseases, WGS was most frequently requested for pediatric patients under the age of 12 years (57.3%). The genetic diagnosis rate for rare diseases was verified to be approximately 31.5% for all patients who underwent testing, accounting for 80.6% of all diagnosed cases in the pediatric age group. This highlights not only the high demand for rare disease diagnosis in the pediatric age group but also the cost-effectiveness and necessity of support for early diagnosis of rare diseases. In addition, the average time required for the healthcare providers who requested the tests to receive the final diagnostic reports was significantly reduced to 28 days, thereby contributing to minimizing delays in genetic diagnosis.
The program provided practical social and economic support through national policies such as special health insurance coverage and healthcare expense assistance for patients with rare diseases to a substantial number of patients diagnosed with rare diseases. Specifically, approximately 30% of patients with positive results were found to have conditions for which treatment methods such as medication and diet therapy exist, suggesting that this program could contribute to early treatment coordination, alleviate the socioeconomic burden on patients and their families, and improve clinical prognosis, going beyond the medical dimension of simple diagnostic support. Genetic testing support for families is also expected to play an important role in establishing a system for early screening and preventive intervention for potential high-risk groups.
The SF analysis results were obtained from 3.9% of patients with rare diseases, which was similar to the SF frequency (3.75%) reported in previous large-scale genome studies in the Republic of Korea [13]. The unexpected findings of pathogenic genetic variants during the WGS-based diagnosis process may have practical clinical significance. The SFs can be used as practical evidence for developing preventive health management strategies that include periodic clinical monitoring of carriers with a potential risk of disease onset and all family members, as well as domestic clinical guidelines [14].
Meanwhile, considering that the average time required for diagnosis of patients diagnosed through WGS was 7.4 years, it seems that patients with rare diseases undergo a long diagnostic journey until obtaining an appropriate diagnosis after the onset of initial symptoms. A particularly salient finding was that a quarter of patients remained undiagnosed for more than 10 years, suggesting limited access to healthcare in regions outside the Seoul metropolitan area and limitations in the genetic diagnosis system. Consequently, these findings underscore the ongoing necessity of a swift and precise genetic diagnostic system for patients with rare diseases. Moreover, they offer substantiation for the imperative of policy and institutional enhancements aimed at averting the forfeiture of treatment opportunities due to protracted diagnostic delays.
However, for patients who remain undiagnosed even through WGS-based diagnostic testing in this program, it will be necessary to pursue additional diagnostic support measures such as periodic reanalysis, trio-based WGS, RNA sequencing, and long-read sequencing. This approach is currently being pursued on an international scale to identify the genetic mechanisms of rare diseases that cannot be diagnosed using existing testing methods. Numerous studies have reported this approach as an effective strategy for elucidating new disease mechanisms [15-17].
In conclusion, the Outreach Support Program for the Diagnosis of Rare Diseases has demonstrated the potential to serve as an effective policy model within the domestic rare disease management system by addressing regional disparities in diagnostic infrastructure. This program facilitates early diagnosis for patients suspected of having rare diseases, regardless of their place of residence. Consequently, treatment coordination and proactive management of high-risk families are enabled. It is noteworthy that all participants in the screening program accessed diagnostic services through healthcare institutions located outside the Seoul metropolitan area. This program is significant in that it contributed to the substantial reduction of regional disparities in access to diagnosis and to improvement in equity (Table 4).
Table 4. Number and proportion of test requests by region (N=410).
| Region | No. of medical institutions | No. of tests | Proportion (%) | Average requests per institution |
|---|---|---|---|---|
| Total | 23 | 410 | 100.0 | - |
| Gangwon | 1 | 34 | 8.30 | 34 |
| Gyeongnam East | 6 | 101 | 24.60 | 17 |
| Gyeongnam West | 2 | 62 | 15.10 | 31 |
| Gyeongbuk | 5 | 28 | 6.80 | 6 |
| Sejong | 1 | 6 | 1.50 | 6 |
| Jeonnam | 1 | 38 | 9.30 | 38 |
| Jeonbuk | 2 | 50 | 12.20 | 25 |
| Jeju | 1 | 13 | 3.20 | 13 |
| Chungnam | 3 | 38 | 9.30 | 13 |
| Chungbuk | 1 | 40 | 9.80 | 40 |
Acknowledgments
None.
Declarations
Ethics Statement: Not applicable.
Funding Source: This study was funded by the Korea Disease Control and Prevention Agency grant (6500-6544-306).
Conflict of Interest: The authors have no conflicts of interest to declare.
Author Contributions: Conceptualization: CKC. Data curation: YEL. Formal analysis: YEL. Funding acquisition: CKC. Investigation: YEL. Methodology: CKC. Project administration: CKC. Resources: CKC. Supervision: CKC. Validation: CKC. Visualization: YEL. Writing – original draft: YEL. Writing – review & editing: JYK, JKC, YBK, CKC.
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