Addressing the diagnostic gap through deep phenotyping.

IF 4.1 3区 医学 Q2 GENETICS & HEREDITY
John Guozhuang Li, Kexin Xu, Bin Xiao, Jingnan Li, Yi-Cheng Zhu, Hongzhong Jin, Qingwei Qi, Lianlei Wang, Lina Zhao, Zhihong Wu, Sen Zhao, Terry Jianguo Zhang, Nan Wu
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引用次数: 0

Abstract

BACKGROUND: Rare diseases remain a substantial challenge for healthcare systems worldwide, and 80% are attributable to genetic factors. Although exome sequencing (ES) and genome sequencing (GS) have become routine and widely accessible in our current clinical practice due to reduced costs and policy support, progress in systematically capturing deep and structured phenotypic data has lagged behind, limiting diagnostic accuracy. Integrating deep phenotyping with genomic analysis may help close the diagnostic gap. However, its value has not been comprehensively assessed in clinical practice, particularly in the absence of a systematic medical geneticist program in our current clinical settings. METHODS: We accessed and reviewed the clinical and sequencing data of patients with a rare or suspected genetic disorder assessed at our center between 2022 and 2024. Through detailed case vignettes, we evaluated how granular bedside data influenced the diagnostic outcomes. Expert consensus and literature review were then used to construct a continually updated Recommended Phenotypes Panel and to build a nine-domain framework termed iDREAMS (integrating Deep phenotyping with genetic analysis for Rare disease Evaluation And Management Strategies). RESULTS: Deep phenotyping uncovered diagnostic clues missed by standard assessments across all nine domains, guiding genome analysis, shortening the diagnostic odyssey, and refining counselling in numerous cases. The panel streamlined data capture for clinicians, improved multidisciplinary case discussions, and fed directly into the iDREAMS framework, offering a reproducible pathway from phenotype to genotype. CONCLUSIONS: Systematic deep phenotyping is pivotal for closing the “sequencing-analysis” gap in rare disease diagnostics. The iDREAMS framework provides a practical, scalable model that enhances diagnostic accuracy, lowers the entry barrier for resource-limited settings, and extends the reach of precision medicine to patients who had long remained undiagnosed.

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通过深度表型解决诊断差距。
背景:罕见病仍然是全球卫生保健系统面临的重大挑战,其中80%可归因于遗传因素。尽管由于降低成本和政策支持,外显子组测序(ES)和基因组测序(GS)在我们当前的临床实践中已经成为常规和广泛可及的方法,但在系统地获取深度和结构化表型数据方面的进展滞后,限制了诊断的准确性。整合深度表型与基因组分析可能有助于缩小诊断差距。然而,其价值尚未在临床实践中得到全面评估,特别是在我们目前临床环境中缺乏系统的医学遗传学家计划的情况下。方法:我们访问并回顾了2022年至2024年间在我们中心评估的罕见或疑似遗传疾病患者的临床和测序数据。通过详细的病例调查,我们评估了床边数据对诊断结果的影响。然后利用专家共识和文献综述构建一个不断更新的推荐表型面板,并建立一个名为iDREAMS的九域框架(将深度表型与罕见病评估和管理策略的遗传分析结合起来)。结果:深度表型揭示了所有九个领域的标准评估所遗漏的诊断线索,指导了基因组分析,缩短了诊断过程,并在许多情况下改进了咨询。该小组简化了临床医生的数据采集,改进了多学科病例讨论,并直接输入iDREAMS框架,提供了从表型到基因型的可重复途径。结论:系统的深度表型分析对于缩小罕见病诊断中“测序-分析”的差距至关重要。iDREAMS框架提供了一个实用的、可扩展的模型,提高了诊断的准确性,降低了资源有限环境的进入门槛,并将精准医疗的范围扩展到长期未被诊断的患者。
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来源期刊
Human Genomics
Human Genomics GENETICS & HEREDITY-
CiteScore
6.00
自引率
2.20%
发文量
55
审稿时长
11 weeks
期刊介绍: Human Genomics is a peer-reviewed, open access, online journal that focuses on the application of genomic analysis in all aspects of human health and disease, as well as genomic analysis of drug efficacy and safety, and comparative genomics. Topics covered by the journal include, but are not limited to: pharmacogenomics, genome-wide association studies, genome-wide sequencing, exome sequencing, next-generation deep-sequencing, functional genomics, epigenomics, translational genomics, expression profiling, proteomics, bioinformatics, animal models, statistical genetics, genetic epidemiology, human population genetics and comparative genomics.
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