A dyadic approach to the delineation of diagnostic entities in clinical genomics.
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ABSTRACT:
SUBMITTER: Biesecker LG
PROVIDER: S-EPMC7820621 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Phenotype-based diagnostic criteria were developed for Proteus syndrome in 1999 and updated in 2006. Subsequently, the causative mosaic gene alteration was discovered, the c.49G>A p.E17K variant in AKT1. As well, a number of overlapping overgrowth disorders attributable to mosaic PIK3CA variants have now been characterized, leading to the designation of PIK3CA-related overgrowth spectrum (PROS). Finally, ongoing work to better characterize Proteus syndrome has led to identification of additional features of that disorder that could be useful in diagnostic criteria. We have taken the opportunity of these discoveries to re-evaluate the Proteus syndrome diagnostic criteria. Here we propose a new set of diagnostic criteria that establishes a weighted, point-based system for the phenotypic attributes and then integrates that with the potential molecular test results to result in one of two designations: AKT1-related Proteus syndrome or AKT1-related overgrowth spectrum. A patient whose only manifestation is an AKT1 c.49G>A-positive tumor would receive neither of these designations. Here we review the rational basis of diagnostic criteria and argue that a unitary diagnostic entity is a distinct gene-phenotype dyad and that this should be the model for all mendelian disorders. The gene-alone or phenotype-alone approach is inadequate to rigorously delineate a unitary diagnostic entity.
| S-EPMC7520016 | biostudies-literature
Project description:IntroductionThe human genome contains the instructions for the development and biological homeostasis of the human organism and the genetic transmission of traits. Genome variation in human populations is the basis of evolution; individual or personal genomes vary tremendously, making each of us truly unique.Areas coveredAssaying this individual variation using genomic technologies has many applications in clinical medicine, from elucidating the biology of disease to designing strategies to ameliorate perturbations from homeostasis. Detecting pathogenic rare variation in a genome may provide a molecular diagnosis that can be informative for patient management and family healthcare.Expert opinionDespite the increasing clinical use of unbiased genomic testing, including chromosome microarray analysis (CMA) with array comparative genomic hybridization (aCGH) or SNP arrays, clinical exome sequencing (cES), and whole-genome sequencing (WGS), to survey genome-wide for molecular aberrations, clinical acumen paired with an understanding of the limitations of each testing type will be needed to achieve molecular diagnoses. Potential opportunities for improving case solved rates, functionally annotating the majority of genes in the human genome, and further understanding genetic contributions to disease will empower clinical genomics and the precision medicine initiative.
| S-EPMC8208305 | biostudies-literature
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.
| S-EPMC9600391 | biostudies-literature
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.
| S-EPMC8323233 | biostudies-literature
Project description:This SuperSeries is composed of the SubSeries listed below.
2021-06-17 | GSE178330 | GEO
Project description:Although genomic research has predominantly relied on phenotypic ascertainment of individuals affected with heritable disease, the falling costs of sequencing allow consideration of genomic ascertainment and reverse phenotyping (the ascertainment of individuals with specific genomic variants and subsequent evaluation of physical characteristics). In this research modality, the scientific question is inverted: investigators gather individuals with a genomic variant and test the hypothesis that there is an associated phenotype via targeted phenotypic evaluations. Genomic ascertainment research is thus a model of predictive genomic medicine and genomic screening. Here, we provide our experience implementing this research method. We describe the infrastructure we developed to perform reverse phenotyping studies, including aggregating a super-cohort of sequenced individuals who consented to recontact for genomic ascertainment research. We assessed 13 studies completed at the National Institutes of Health (NIH) that piloted our reverse phenotyping approach. The studies can be broadly categorized as (1) facilitating novel genotype-disease associations, (2) expanding the phenotypic spectra, or (3) demonstrating ex vivo functional mechanisms of disease. We highlight three examples of reverse phenotyping studies in detail and describe how using a targeted reverse phenotyping approach (as opposed to phenotypic ascertainment or clinical informatics approaches) was crucial to the conclusions reached. Finally, we propose a framework and address challenges to building collaborative genomic ascertainment research programs at other institutions. Our goal is for more researchers to take advantage of this approach, which will expand our understanding of the predictive capability of genomic medicine and increase the opportunity to mitigate genomic disease.
| S-EPMC9892776 | biostudies-literature
Project description:In molecular profiling studies of cancer patients, experimental and clinical data are combined in order to understand the clinical heterogeneity of the disease: clinical information for each subject needs to be linked to tumour samples, macromolecules extracted, and experimental results. This may involve the integration of clinical data sets from several different sources: these data sets may employ different data definitions and some may be incomplete.In this work we employ semantic web techniques developed within the CancerGrid project, in particular the use of metadata elements and logic-based inference to annotate heterogeneous clinical information, integrate and query it.We show how this integration can be achieved automatically, following the declaration of appropriate metadata elements for each clinical data set; we demonstrate the practicality of this approach through application to experimental results and clinical data from five hospitals in the UK and Canada, undertaken as part of the METABRIC project (Molecular Taxonomy of Breast Cancer International Consortium).We describe a metadata approach for managing similarities and differences in clinical datasets in a standardized way that uses Common Data Elements (CDEs). We apply and evaluate the approach by integrating the five different clinical datasets of METABRIC.
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Project description:Campylobacter ureolyticus is an emerging pathogen increasingly appreciated as a common cause of gastroenteritis and extra-intestinal infections in humans. Outside the setting of gastroenteritis, little work has been done to describe the genomic content and relatedness of the species, especially regarding clinical isolates. We reviewed the epidemiology of clinical C. ureolyticus cultured by our institution over the past 10 years. Fifty-one unique C. ureolyticus isolates were identified between January 2010 and August 2022, mostly originating from abscesses and blood cultures. To clarify the taxonomic relationships between isolates and to attribute specific genes with different clinical manifestations, we sequenced 19 available isolates from a variety of clinical specimen types and conducted a pangenomic analysis with publicly available C. ureolyticus genomes. Digital DNA:DNA hybridization suggested that these C. ureolyticus comprised a species complex of 10 species clusters (SCs) and several subspecies clusters. Although some orthologous genes or gene functions were enriched in isolates found in different SCs and clinical specimens, no association was significant. Nearly a third of the isolates possessed antimicrobial resistance genes, including the ermA resistance gene, potentially conferring resistance to macrolides, the treatment of choice for severe human campylobacteriosis. This work effectively doubles the number of publicly available C. ureolyticus genomes, provides further clarification of taxonomic relationships within this bacterial complex, and identifies target SCs for future analysis.
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