Characterizing Long COVID: Deep Phenotype of a Complex Condition.
Characterizing Long COVID: Deep Phenotype of a Complex Condition.
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DOI：
10.1016/j.ebiom.2021.103722
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发表时间：
2021-12
期刊：
影响因子：
11.1
通讯作者：
Robinson PN
中科院分区：
文献类型：
--
作者：
Deer RR;Rock MA;Vasilevsky N;Carmody L;Rando H;Anzalone AJ;Basson MD;Bennett TD;Bergquist T;Boudreau EA;Bramante CT;Byrd JB;Callahan TJ;Chan LE;Chu H;Chute CG;Coleman BD;Davis HE;Gagnier J;Greene CS;Hillegass WB;Kavuluru R;Kimble WD;Koraishy FM;Köhler S;Liang C;Liu F;Liu H;Madhira V;Madlock-Brown CR;Matentzoglu N;Mazzotti DR;McMurry JA;McNair DS;Moffitt RA;Monteith TS;Parker AM;Perry MA;Pfaff E;Reese JT;Saltz J;Schuff RA;Solomonides AE;Solway J;Spratt H;Stein GS;Sule AA;Topaloglu U;Vavougios GD;Wang L;Haendel MA;Robinson PN
许多出版物描述了SARS-CoV-2（PASC或“长期COVID”）急性后后遗症的临床表现，但由于方法异质性和缺乏表示许多表型表现的标准，因此难以整合。患者主导的研究对于了解COVID-19的自然史特别重要，但由于它们经常使用不同的术语来描述相同的症状或病症，因此整合受到阻碍。患者与临床表征的这种显著差异促使提出了指定表现的本体论方法，这将改善未来长期COVID研究的捕获和整合。人类表型本体（Human Phenotype Ontology，HPO）是一种广泛用于交换和分析人类疾病表型异常的标准，但尚未应用于COVID-19的分析。我们识别了2021年4月29日之前发表的303篇文章，整理了59篇相关手稿，这些手稿描述了急性COVID-19后三周或更长时间内81个队列的临床表现，并将287个独特的临床发现映射到HPO术语。我们提出了外行同义词和定义，可用于连接患者自我报告问卷的标准医学术语。长期的COVID临床表现在不同的研究中没有得到一致的评估，并且不同的作者报告了大多数表现的广泛同义词。在至少10个队列中，作者报告了31个与HPO术语对应的独特临床特征;最常报告的特征是疲劳（中位数45.1%），最不常报告的是恶心（中位数3.9%），但报告的百分比在研究之间差异很大。将长期COVID表现转化为可计算的HPO术语将改善长期COVID患者的分析、数据捕获和分类。如果研究人员、临床医生和患者有共同的语言，那么研究可以更有效地进行比较/汇总。此外，将非专业术语映射到HPO将有助于患者协助临床医生和研究人员创建可通过计算获得的表型特征，从而改善长期COVID的分层、诊断和治疗。U24TR002306; UL1TR001439; P30AG024832; GBMF4552; R01HG010067; UL1TR002535; K23HL128909; UL1TR002389; K99GM145411。
Numerous publications describe the clinical manifestations of post-acute sequelae of SARS-CoV-2 (PASC or “long COVID”), but they are difficult to integrate because of heterogeneous methods and the lack of a standard for denoting the many phenotypic manifestations. Patient-led studies are of particular importance for understanding the natural history of COVID-19, but integration is hampered because they often use different terms to describe the same symptom or condition. This significant disparity in patient versus clinical characterization motivated the proposed ontological approach to specifying manifestations, which will improve capture and integration of future long COVID studies. The Human Phenotype Ontology (HPO) is a widely used standard for exchange and analysis of phenotypic abnormalities in human disease but has not yet been applied to the analysis of COVID-19. We identified 303 articles published before April 29, 2021, curated 59 relevant manuscripts that described clinical manifestations in 81 cohorts three weeks or more following acute COVID-19, and mapped 287 unique clinical findings to HPO terms. We present layperson synonyms and definitions that can be used to link patient self-report questionnaires to standard medical terminology. Long COVID clinical manifestations are not assessed consistently across studies, and most manifestations have been reported with a wide range of synonyms by different authors. Across at least 10 cohorts, authors reported 31 unique clinical features corresponding to HPO terms; the most commonly reported feature was Fatigue (median 45.1%) and the least commonly reported was Nausea (median 3.9%), but the reported percentages varied widely between studies. Translating long COVID manifestations into computable HPO terms will improve analysis, data capture, and classification of long COVID patients. If researchers, clinicians, and patients share a common language, then studies can be compared/pooled more effectively. Furthermore, mapping lay terminology to HPO will help patients assist clinicians and researchers in creating phenotypic characterizations that are computationally accessible, thereby improving the stratification, diagnosis, and treatment of long COVID. U24TR002306; UL1TR001439; P30AG024832; GBMF4552; R01HG010067; UL1TR002535; K23HL128909; UL1TR002389; K99GM145411 .
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DOI：
10.1530/vb-20-0017
发表时间：
2021
期刊：
Vascular biology (Bristol, England)
影响因子：
--
作者：
Giordo R;Paliogiannis P;Mangoni AA;Pintus G
通讯作者：
Pintus G
影响因子：
14.9
作者：
Köhler S;Gargano M;Matentzoglu N;Carmody LC;Lewis-Smith D;Vasilevsky NA;Danis D;Balagura G;Baynam G;Brower AM;Callahan TJ;Chute CG;Est JL;Galer PD;Ganesan S;Griese M;Haimel M;Pazmandi J;Hanauer M;Harris NL;Hartnett MJ;Hastreiter M;Hauck F;He Y;Jeske T;Kearney H;Kindle G;Klein C;Knoflach K;Krause R;Lagorce D;McMurry JA;Miller JA;Munoz-Torres MC;Peters RL;Rapp CK;Rath AM;Rind SA;Rosenberg AZ;Segal MM;Seidel MG;Smedley D;Talmy T;Thomas Y;Wiafe SA;Xian J;Yüksel Z;Helbig I;Mungall CJ;Haendel MA;Robinson PN
通讯作者：
Robinson PN
影响因子：
7.2
作者：
Hopkins, Claire;Surda, Pavol;Kumar, Nirmal
通讯作者：
Kumar, Nirmal
DOI：
10.1073/pnas.2100766118
发表时间：
2021-06-08
影响因子：
11.1
作者：
Lever J;Altman RB
通讯作者：
Altman RB
影响因子：
15.1
作者：
Bansal, A. S.;Bradley, A. S.;Ford, B.
通讯作者：
Ford, B.