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A dyadic approach to the delineation of diagnostic entities in clinical genomics.

ABSTRACT: The delineation of disease entities is complex, yet recent advances in the molecular characterization of diseases provide opportunities to designate diseases in a biologically valid manner. Here, we have formalized an approach to the delineation of Mendelian genetic disorders that encompasses two distinct but inter-related concepts: (1) the gene that is mutated and (2) the phenotypic descriptor, preferably a recognizably distinct phenotype. We assert that only by a combinatorial or dyadic approach taking both of these attributes into account can a unitary, distinct genetic disorder be designated. We propose that all Mendelian disorders should be designated as "GENE-related phenotype descriptor" (e.g., "CFTR-related cystic fibrosis"). This approach to delineating and naming disorders reconciles the complexity of gene-to-phenotype relationships in a simple and clear manner yet communicates the complexity and nuance of these relationships.

SUBMITTER: Biesecker LG

PROVIDER: S-EPMC7820621 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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A dyadic approach to the delineation of diagnostic entities in clinical genomics.

Biesecker Leslie G LG Adam Margaret P MP Alkuraya Fowzan S FS Amemiya Anne R AR Bamshad Michael J MJ Beck Anita E AE Bennett James T JT Bird Lynne M LM Carey John C JC Chung Brian B Clark Robin D RD Cox Timothy C TC Curry Cynthia C Dinulos Mary Beth Palko MBP Dobyns William B WB Giampietro Philip F PF Girisha Katta M KM Glass Ian A IA Graham John M JM Gripp Karen W KW Haldeman-Englert Chad R CR Hall Bryan D BD Innes A Micheil AM Kalish Jennifer M JM Keppler-Noreuil Kim M KM Kosaki Kenjiro K Kozel Beth A BA Mirzaa Ghayda M GM Mulvihill John J JJ Nowaczyk Malgorzata J M MJM Pagon Roberta A RA Retterer Kyle K Rope Alan F AF Sanchez-Lara Pedro A PA Seaver Laurie H LH Shieh Joseph T JT Slavotinek Anne M AM Sobering Andrew K AK Stevens Cathy A CA Stevenson David A DA Tan Tiong Yang TY Tan Wen-Hann WH Tsai Anne C AC Weaver David D DD Williams Marc S MS Zackai Elaine E Zarate Yuri A YA

American journal of human genetics 20210101 1

The delineation of disease entities is complex, yet recent advances in the molecular characterization of diseases provide opportunities to designate diseases in a biologically valid manner. Here, we have formalized an approach to the delineation of Mendelian genetic disorders that encompasses two distinct but inter-related concepts: (1) the gene that is mutated and (2) the phenotypic descriptor, preferably a recognizably distinct phenotype. We assert that only by a combinatorial or dyadic approa ...[more]

PMID: 33417889

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Project description:Background: A long list of syndromic entities can be diagnosed immediately through scrutinizing the clinical phenotype of the craniofacial features. The latter should be assisted via proper radiological interpretations. Patients and Methods: Different children aged from 1 month to 12 years were referred to our departments seeking orthopedic advice. Primarily, all received variable false diagnoses in other institutes. Two unrelated boys of one month and 12 months were falsely diagnosed as having positional plagiocephaly associated with contractures of idiopathic origin. Two unrelated boys of 14 months and 2 years were diagnosed with pseudo-hydrocephalus and non-specific syndrome, and were referred to explore their skeletal development. Two unrelated girls of 4 years old and 12 years old presented with multiple contractures were referred because of progressive scoliosis. A 4-year-old girl was referred with a false provisional diagnosis of facial diplegia. All children underwent detailed clinical, radiological and tomographic phenotypic characterizations and genetic testing, respectively. Results: Idaho syndrome (craniosynostosis associated with multiple dislocations) was the final diagnosis in the two unrelated boys with plagiocephaly and multiple contractures. Two children falsely diagnosed with pseudo-hydrocephalus and non-specific syndrome, were diagnosed with Silver-Russell syndrome (RSS). Contractural arachnodactyly Beals (CAB) was confirmed as the definitive diagnosis in the two unrelated girls with progressive scoliosis and multiple contractures. Parry-Romberg syndrome (PRS) associated with congenital lumbar kyphosis was the final diagnosis of the girl with the diagnosis of facial diplegia. Hypomethylation of ICR1 was confirmed in the RSS patients. Whole exome sequencing (WES) revealed a heterozygous mutation in the PRS patients. WES and array-CGH showed that no relevant variants or copy number variations (CNV) were identified in the CAB patients. Conclusions: On the one hand, newborn children can manifest diverse forms of abnormal craniofacial features, which are usually associated with either major or minor dysmorphic stigmata. A cleft lip/ palate is a major craniofacial malformation, and frontal bossing or a disproportionate craniofacial contour can be falsely considered as a transient plagiocephaly, which is spontaneously resolved by time. On the other hand, many physicians fall into the problem of deeming a countless number of diseases, such as contractures, as an idiopathic or non-specific syndrome. The latter stems from limited clinical experience. Therefore, failing to establish between the onset of the deformity and other inexplicit abnormal features that the patient or their immediate families or relatives carry is the final outcome. In this study, we used, for the first time, a reconstruction CT scan to further delineate the congenital disruption of the craniofacial anatomy and the other skeletal malformation complex.

Project description:BackgroundComputed tomography (CT) reports record a large volume of valuable information about patients' conditions and the interpretations of radiology images from radiologists, which can be used for clinical decision-making and further academic study. However, the free-text nature of clinical reports is a critical barrier to use this data more effectively. In this study, we investigate a novel deep learning method to extract entities from Chinese CT reports for lung cancer screening and TNM staging.MethodsThe proposed approach presents a new named entity recognition algorithm, namely the BERT-based-BiLSTM-Transformer network (BERT-BTN) with pre-training, to extract clinical entities for lung cancer screening and staging. Specifically, instead of traditional word embedding methods, BERT is applied to learn the deep semantic representations of characters. Following the long short-term memory layer, a Transformer layer is added to capture the global dependencies between characters. Besides, pre-training technique is employed to alleviate the problem of insufficient labeled data.ResultsWe verify the effectiveness of the proposed approach on a clinical dataset containing 359 CT reports collected from the Department of Thoracic Surgery II of Peking University Cancer Hospital. The experimental results show that the proposed approach achieves an 85.96% macro-F1 score under exact match scheme, which improves the performance by 1.38%, 1.84%, 3.81%,4.29%,5.12%,5.29% and 8.84% compared to BERT-BTN, BERT-LSTM, BERT-fine-tune, BERT-Transformer, FastText-BTN, FastText-BiLSTM and FastText-Transformer, respectively.ConclusionsIn this study, we developed a novel deep learning method, i.e., BERT-BTN with pre-training, to extract the clinical entities from Chinese CT reports. The experimental results indicate that the proposed approach can efficiently recognize various clinical entities about lung cancer screening and staging, which shows the potential for further clinical decision-making and academic research.

Dataset Information

A dyadic approach to the delineation of diagnostic entities in clinical genomics.

Publications

A dyadic approach to the delineation of diagnostic entities in clinical genomics.

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