Coffin-Siris 증후군: 유전형-표현형 상관관계 군집 분석 및 새로운 변이
Coffin-Siris Syndrome: Genotype-Phenotype Clustering and Novel Variants
서울대학교 의과대학 서울대학교병원 진단검사의학과1, 서울대학교병원 의생명연구원2
Department of Laboratory Medicine1, Seoul National University Hospital, Seoul National University College of Medicine, Seoul; Biomedical Research Institute2, Seoul National University Hospital, Seoul, KoreaCorrespondence to:
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Lab Med Online 2023; 13(2): 91-96
Published April 1, 2023
Copyright © The Korean Society for Laboratory Medicine.
방법: 우리는 2017년 1월부터 2020년 12월까지 질병관리청 희귀 질환 진단 프로그램에 등록한 23명의 CSS 의심환자의 whole exome sequencing (WES) 보고서를 포함한 의무기록을 후향적으로 검토하였다. 통계 분석을 위해R 버전 4.2.0을 이용하여 Jaccard/Tanimoto 유사성 검정을 통한 군집 분석을 수행하였다.
결과: 8건의 증례가 CSS로 진단되었다. ARID1B (NM_020732.3) Gln958*, Asn1320*, Gly1696* 및 Gly806Trpfs*, SMARCA4 (NM_001128849.1) Asn916Ser의 5가지 증례에서 새로운 변이가 확인되었다. 모든 ARID1B 증례에서 발작 등의 중추신경계 증상이 관찰되었고, 모든 SMARCA4 증례에서 다섯 번째 수족지의 저형성이 관찰되었다. SMARCA4 Asn916Ser은 de novo로 확인되었다. 유전형-표현형 분석에서 비교적 새로운 접근법인 군집 분석을 통해 증례들 간의 유사성 네트워크가 존재함을 확인하였다.
결론: 우리는 CSS로 진단된 8명의 환자를 보고했으며 그 중 5명에서 ARID1B 또는 SMARCA4의 새로운 병원성 변이를 확인하였다. 본 연구는 유전자형-표현형 군집 분석 및 새로운 변이의 보고를 통해 CSS의 진단 및 분류 범주를 더욱 정교화하고, 향후 CSS에 대한 임상적 진단 기준을 명확히 하는 데 기여할 것으로 기대된다. 이 연구는 ARID1B 또는 SMARCA4에 의한 CSS의 표현형을 설명하는 데 기여한다. 이전에 잘 알려지지 않은 희귀 질환에 WES와 같은 보다 심층적인 유전자 검사가 적용됨에 따라 향후 연구에서는 전형적이지 않은 형질을 나타내는 환자에서 CSS를 더 용이하게 진단할 수 있을 것이다. 분자유전학적 검사를 통해 유전적 진단, 임상증상, 본 희귀질환의 분류 및 기준에 대한 추가 연구가 요구된다.
Methods: We retrospectively reviewed the medical records of 23 suspected patients with CSS enrolled in the rare disease diagnostic program of the Korean Disease Control and Prevention Agency from January 2017 to December 2020, including whole-exome sequencing (WES) reports. Statistical analysis was performed using cluster analysis through Jaccard/Tanimoto similarity test using the R version 4.2.0.
Results: Eight cases were genetically diagnosed with the CSS. Five cases were identified to have a novel variant: ARID1B (NM_020732.3) Gln958*, Asn1320*, Gly1696*, Gly806Trpfs*, and SMARCA4 (NM_001128849.1) Asn916Ser. Central nervous system symptoms were observed in all ARID1B cases, and the fifth digit hypoplasia was observed in all SMARCA4 cases. SMARCA4 Asn916Ser was identified as de novo. A similarity network was identified using cluster analysis, a relatively fresh approach to genotype-phenotype analysis.
Conclusions: We reported eight patients diagnosed with CSS, five of whom have novel genetic variants of ARID1B or SMARCA4. A novel case of SMARCA4 was de novo. This study contributes to describing the CSS phenotype. Future studies may facilitate easier diagnosis of CSS in patients who present with atypical traits as more in-depth genetic testing, such as WES, is applied to rare disorders.
Coffin-Siris syndrome (CSS, MIM 135900) is a disorder characterized by distal phalanx, nail hypoplasia, or aplasia of the fifth finger or toe (digit), which may be accompanied by developmental or cognitive delay, characteristic facial features, hypotonia, hypertrichosis, microcephaly, and organ system abnormalities [1, 2]. The syndrome is caused by variants in several genes which are encoding components of Brahma-related gene 1 (BRG1)/ Brahma homologue (BRM)-Associated Factor (BAF) complex , which is one of the chromatin-remodeling complex families known in mammals [4, 5]. These genes include
A genotype-phenotype correlation study is an effective way to relate individual genetic backgrounds to specific diseases or characteristics, and is the basis of precision and genomic medicine . The purpose of this study was to analyze genotype-phenotype correlations in patients with suspected developmental delay (DD) and intellectual disability (ID), and clinically suspected CSS, and to identify novel variants. This study was approved by the Institutional Review Board (IRB) of Seoul National University Hospital (IRB No. 2204-161-1320) under the Helsinki Declaration.
MATERIALS AND METHODS
This retrospective study reviewed the electronic medical records of 23 suspected patients with CSS enrolled in a rare disease diagnostic program of the Korean Disease Control and Prevention Agency (KDCA) from January 2017 to December 2020. Patients were enrolled when they exhibited the following signs or symptoms, and demonstrated potential clinically suspected CSS: dysplasia of either the distal phalanx or the nail of the fifth digit, DD, ID, coarse facial features, hypertrichosis, seizures, and central nervous system (CNS) malformations. Among the 23 patients with suspected CSS, who requested for a rare disease diagnostic program, eight cases reported positive for CSS were included, and the remaining patients were excluded. For the CSS positive patients, basic information (reason for test, test date, diagnosis, age at diagnosis, sex), clinical manifestations (such as finger or toe hypoplasia, DD/ID, characteristic facial findings, hypotonia, scalp hair condition, cardiac anomaly, gastrointestinal tract anomaly, and CNS anomaly), and laboratory test results (reports from rare disease diagnostic program) were collected retrospectively from electronic medical records.
In the rare disease diagnosis program, whole-exome sequencing (WES), Sanger sequencing and multiplex ligation dependent probe amplification was performed. Then, variants were classified based on the American College of Medical Genetics and Genomics and the Association for Molecular Pathology guidelines .
The R version 4.2.0 (R Core Team, Vienna, Austria) was used for statistical analysis. The frequency and ratio of binary phenotypes per gene were calculated and visualized. A cluster analysis using Jaccard/Tanimoto similarity test  was performed to confirm if the cluster was formed according to genotype-phenotype, and the significance of the clusters. The Jaccard/Tanimoto coefficient is the ratio of union to intersection and is used to measure the similarity between binary data . The network between clusters was expressed as a graph using the calculated
The frequency of variant types and phenotypes for each causative gene is summarized in Table 1. In
In Fig. 1A, the frequency of phenotypes observed by each gene is expressed as a bar plot. In the combination of cases, the number of phenotypes shared by the two cases was expressed as a matrix (Fig. 1B), and five phenotypes were observed identically in three cases of
Figure 1. Frequency of phenotypes observed using gene and cluster analysis. (A) The frequency of phenotypes observed in each causative gene was expressed as a percentage of the total cases of each gene. (B) The number of same phenotypes observed in the combination of cases was expressed as a matrix. (C) A dendrogram based on the matrix depicted in (B). (D) Cluster analysis using Jaccard/Tanimoto similarity test for (B). (E) Networks with significant phenotypic similarities between each case was plotted as a graph based on the matrix depicted in (D), when the
P≤0.01 was applied to (D) as a cutoff. The distance between each node is meaningless.
Abbreviations: DD/ID, developmental delay/intellectual disability; GI, gastrointestinal; GU, genitourinary; CNS, central nervous system.
To the best of our knowledge, five novel variants were identified in this study (Table 2). In
In this study, we confirmed that a subgroup of
CSS is a genetically heterogeneous disease, and it has been previously established that the variants of
There are some caveats in interpreting the results of this study. First, there may be limitations in generalization because the sample size is too small and patients were tested according to their clinical manifestation; one alternative solution is to analyze multi-omics together with genomic information. Second, a cluster with similar phenotypic networks was identified in a subset of specific causative genes, but owing to the nature of the retrospective study, CSS phenotypes that are not mentioned in the electronic medical record may exist, which may lead to changes in phenotypic networks and consequently, new clusters may emerge or existing clusters may disappear. Thus, it is expected that the cases that formed a single-member cluster in this study could be reclassified according to additional phenotypic information.
In conclusion, we reported four patients with a novel
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