Table_1_Curation and expansion of the Human Phenotype Ontology for systemic autoinflammatory diseases improves phenotype-driven disease-matching.xlsx

IntroductionAccurate and standardized phenotypic descriptions are essential in diagnosing rare diseases and discovering new diseases, and the Human Phenotype Ontology (HPO) system was developed to provide a rich collection of hierarchical phenotypic descriptions. However, although the HPO terms for inborn errors of immunity have been improved and curated, it has not been investigated whether this curation improves the diagnosis of systemic autoinflammatory disease (SAID) patients. Here, we aimed to study if improved HPO annotation for SAIDs enhanced SAID identification and to demonstrate the potential of phenotype-driven genome diagnostics using curated HPO terms for SAIDs.MethodsWe collected HPO terms from 98 genetically confirmed SAID patients across eight different European SAID expertise centers and used the LIRICAL (Likelihood Ratio Interpretation of Clinical Abnormalities) computational algorithm to estimate the effect of HPO curation on the prioritization of the correct SAID for each patient.ResultsOur results show that the percentage of correct diagnoses increased from 66% to 86% and that the number of diagnoses with the highest ranking increased from 38 to 45. In a further pilot study, curation also improved HPO-based whole-exome sequencing (WES) analysis, diagnosing 10/12 patients before and 12/12 after curation. In addition, the average number of candidate diseases that needed to be interpreted decreased from 35 to 2.DiscussionThis study demonstrates that curation of HPO terms can increase identification of the correct diagnosis, emphasizing the high potential of HPO-based genome diagnostics for SAIDs.

精准且标准化的表型描述对于罕见病的诊断以及新疾病的发现至关重要，为此人类表型本体（HPO）系统被开发出来，以提供丰富且层次分明的表型描述集合。尽管HPO术语针对先天性免疫缺陷病已经得到优化和整理，但尚未对此整理是否能够提高系统性自身炎症性疾病（SAID）患者的诊断水平进行探究。本研究旨在探讨优化后的HPO注释是否能提高SAID的识别能力，并展示利用经过整理的HPO术语进行表型驱动基因组诊断的潜力。方法：我们从八个不同欧洲SAID专业中心收集了98例遗传学确认的SAID患者的HPO术语，并利用LIRICAL（临床异常似然比解释）计算算法评估HPO整理对每个患者正确SAID优先级的影响。结果：我们的研究结果显示，正确诊断的比例从66%提升至86%，且最高排名的诊断数量从38增加到45。在进一步的小型研究中，整理工作也提高了基于HPO的全外显子组测序（WES）分析，诊断成功率在整理前后分别从10/12提升至12/12。此外，平均需要解释的候选疾病数量从35减少至2。讨论：本研究表明，HPO术语的整理可以提升正确诊断的识别率，凸显了基于HPO的基因组诊断在SAID中的巨大潜力。