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在 COVID-19 中期,不同的血液炎症生物标志物簇可对宿主表型进行分层。

Distinct blood inflammatory biomarker clusters stratify host phenotypes during the middle phase of COVID-19.

机构信息

The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., 6720A Rockledge Dr, Bethesda, MD, 20817, USA.

Department of Pathology, Uniformed Services University of the Health Sciences, Bethesda, MD, USA.

出版信息

Sci Rep. 2022 Dec 28;12(1):22471. doi: 10.1038/s41598-022-26965-7.

Abstract

The associations between clinical phenotypes of coronavirus disease 2019 (COVID-19) and the host inflammatory response during the transition from peak illness to convalescence are not yet well understood. Blood plasma samples were collected from 129 adult SARS-CoV-2 positive inpatient and outpatient participants between April 2020 and January 2021, in a multi-center prospective cohort study at 8 military hospitals across the United States. Plasma inflammatory protein biomarkers were measured in samples from 15 to 28 days post symptom onset. Topological Data Analysis (TDA) was used to identify patterns of inflammation, and associations with peak severity (outpatient, hospitalized, ICU admission or death), Charlson Comorbidity Index (CCI), and body mass index (BMI) were evaluated using logistic regression. The study population (n = 129, 33.3% female, median 41.3 years of age) included 77 outpatient, 31 inpatient, 16 ICU-level, and 5 fatal cases. Three distinct inflammatory biomarker clusters were identified and were associated with significant differences in peak disease severity (p < 0.001), age (p < 0.001), BMI (p < 0.001), and CCI (p = 0.001). Host-biomarker profiles stratified a heterogeneous population of COVID-19 patients during the transition from peak illness to convalescence, and these distinct inflammatory patterns were associated with comorbid disease and severe illness due to COVID-19.

摘要

新型冠状病毒疾病 2019(COVID-19)的临床表型与从疾病高峰向康复期过渡期间宿主炎症反应之间的关系尚不清楚。本多中心前瞻性队列研究于 2020 年 4 月至 2021 年 1 月在美国 8 家军事医院招募了 129 名成年 SARS-CoV-2 阳性住院和门诊参与者,收集了他们的血浆样本。在症状出现后 15-28 天检测了样本中的血浆炎症蛋白生物标志物。采用拓扑数据分析(TDA)来识别炎症模式,并使用逻辑回归评估与峰值严重程度(门诊、住院、入住 ICU 或死亡)、Charlson 合并症指数(CCI)和体重指数(BMI)的关联。研究人群(n=129,33.3%为女性,中位年龄 41.3 岁)包括 77 名门诊患者、31 名住院患者、16 名 ICU 级患者和 5 名死亡患者。确定了三个不同的炎症生物标志物簇,这些标志物簇与疾病严重程度峰值(p<0.001)、年龄(p<0.001)、BMI(p<0.001)和 CCI(p=0.001)存在显著差异。宿主生物标志物谱对 COVID-19 患者从疾病高峰向康复期过渡期间的异质人群进行了分层,这些不同的炎症模式与合并症和 COVID-19 引起的严重疾病有关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/54f1/9797487/75b07c3db886/41598_2022_26965_Fig1_HTML.jpg

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