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生物衰老预示着英国生物银行参与者对新冠病毒疾病严重程度的易感性。

Biological Aging Predicts Vulnerability to COVID-19 Severity in UK Biobank Participants.

作者信息

Kuo Chia-Ling, Pilling Luke C, Atkins Janice L, Masoli Jane A H, Delgado João, Tignanelli Christopher, Kuchel George A, Melzer David, Beckman Kenneth B, Levine Morgan E

机构信息

Connecticut Convergence Institute for Translation in Regenerative Engineering, University of Connecticut Health, Farmington, USA.

University of Connecticut Center on Aging, School of Medicine, Farmington, USA.

出版信息

J Gerontol A Biol Sci Med Sci. 2021 Jul 13;76(8):e133-e141. doi: 10.1093/gerona/glab060.

Abstract

BACKGROUND

Age and disease prevalence are the 2 biggest risk factors for Coronavirus disease 2019 (COVID-19) symptom severity and death. We therefore hypothesized that increased biological age, beyond chronological age, may be driving disease-related trends in COVID-19 severity.

METHODS

Using the UK Biobank England data, we tested whether a biological age estimate (PhenoAge) measured more than a decade prior to the COVID-19 pandemic was predictive of 2 COVID-19 severity outcomes (inpatient test positivity and COVID-19-related mortality with inpatient test-confirmed COVID-19). Logistic regression models were used with adjustment for age at the pandemic, sex, ethnicity, baseline assessment centers, and preexisting diseases/conditions.

RESULTS

Six hundred and thirteen participants tested positive at inpatient settings between March 16 and April 27, 2020, 154 of whom succumbed to COVID-19. PhenoAge was associated with increased risks of inpatient test positivity and COVID-19-related mortality (ORMortality = 1.63 per 5 years, 95% CI: 1.43-1.86, p = 4.7 × 10-13) adjusting for demographics including age at the pandemic. Further adjustment for preexisting diseases/conditions at baseline (ORM = 1.50, 95% CI: 1.30-1.73 per 5 years, p = 3.1 × 10-8) and at the early pandemic (ORM = 1.21, 95% CI: 1.04-1.40 per 5 years, p = .011) decreased the association.

CONCLUSIONS

PhenoAge measured in 2006-2010 was associated with COVID-19 severity outcomes more than 10 years later. These associations were partly accounted for by prevalent chronic diseases proximate to COVID-19 infection. Overall, our results suggest that aging biomarkers, like PhenoAge may capture long-term vulnerability to diseases like COVID-19, even before the accumulation of age-related comorbid conditions.

摘要

背景

年龄和疾病患病率是2019冠状病毒病(COVID-19)症状严重程度和死亡的两大最大风险因素。因此,我们推测,除了实足年龄外,生物学年龄的增加可能推动了COVID-19严重程度与疾病相关的趋势。

方法

利用英国生物银行英格兰数据,我们测试了在COVID-19大流行前十多年测量的生物学年龄估计值(PhenoAge)是否能预测两种COVID-19严重程度结果(住院检测阳性以及住院检测确诊为COVID-19的与COVID-19相关的死亡率)。使用逻辑回归模型,并对大流行时的年龄、性别、种族、基线评估中心以及既往疾病/状况进行了调整。

结果

2020年3月16日至4月27日期间,613名参与者在住院环境中检测呈阳性,其中154人死于COVID-19。在对包括大流行时年龄在内的人口统计学因素进行调整后,PhenoAge与住院检测阳性风险和COVID-19相关死亡率增加相关(死亡率优势比=每5年1.63,95%置信区间:1.43-1.86,p=4.7×10-13)。对基线时(优势比=1.50,95%置信区间:每5年1.30-1.73,p=3.1×10-8)和大流行早期(优势比=1.21,95%置信区间:每5年1.04-1.40,p=0.011)的既往疾病/状况进行进一步调整后,这种关联有所减弱。

结论

2006年至2010年测量的PhenoAge与十多年后的COVID-19严重程度结果相关。这些关联部分由COVID-19感染附近的常见慢性病所解释。总体而言,我们的结果表明,像PhenoAge这样的衰老生物标志物可能在与年龄相关的合并症积累之前,就能反映出对COVID-19等疾病的长期易感性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/516e/8277080/2bb54201a8b0/glab060f0001.jpg

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