Kuo Chia-Ling, Pilling Luke C, Atkins Janice L, Masoli Jane Ah, Delgado João, Tignanelli Christopher, Kuchel George A, Melzer David, Beckman Kenneth B, Levine Morgan E
Connecticut Convergence Institute for Translation in Regenerative Engineering, University of Connecticut Health, Farmington, Connecticut, USA.
University of Connecticut Center on Aging, School of Medicine, Farmington, Connecticut, USA.
medRxiv. 2020 Jul 11:2020.07.10.20147777. doi: 10.1101/2020.07.10.20147777.
With no known treatments or vaccine, COVID-19 presents a major threat, particularly to older adults, who account for the majority of severe illness and deaths. The age-related susceptibility is partly explained by increased comorbidities including dementia and type II diabetes [1]. While it is unclear why these diseases predispose risk, we hypothesize that increased biological age, rather than chronological age, may be driving disease-related trends in COVID-19 severity with age. To test this hypothesis, we applied our previously validated biological age measure (PhenoAge) [2] composed of chronological age and nine clinical chemistry biomarkers to data of 347,751 participants from a large community cohort in the United Kingdom (UK Biobank), recruited between 2006 and 2010. Other data included disease diagnoses (to 2017), mortality data (to 2020), and the UK national COVID-19 test results (to May 31, 2020) [3]. Accelerated aging 10-14 years prior to the start of the COVID-19 pandemic was associated with test positivity (OR=1.15 per 5-year acceleration, 95% CI: 1.08 to 1.21, p=3.2×10) and all-cause mortality with test-confirmed COVID-19 (OR=1.25, per 5-year acceleration, 95% CI: 1.09 to 1.44, p=0.002) after adjustment for demographics including current chronological age and pre-existing diseases or conditions. The corresponding areas under the curves were 0.669 and 0.803, respectively. Biological aging, as captured by PhenoAge, is a better predictor of COVID-19 severity than chronological age, and may inform risk stratification initiatives, while also elucidating possible underlying mechanisms, particularly those related to inflammaging.
由于尚无已知的治疗方法或疫苗，新冠病毒病构成了重大威胁，尤其对老年人而言，他们占严重疾病和死亡的大多数。与年龄相关的易感性部分可由包括痴呆症和II型糖尿病在内的合并症增加来解释[1]。虽然尚不清楚这些疾病为何会增加风险，但我们推测，增加的生物学年龄而非实际年龄，可能推动了新冠病毒病严重程度随年龄增长的相关趋势。为了验证这一假设，我们将之前经过验证的由实际年龄和九种临床化学生物标志物组成的生物学年龄测量方法（PhenoAge）[2]应用于来自英国一个大型社区队列（英国生物银行）的347,751名参与者的数据，这些参与者于2006年至2010年招募。其他数据包括疾病诊断（截至2017年）、死亡率数据（截至2020年）以及英国全国新冠病毒病检测结果（截至2020年5月31日）[3]。在调整了包括当前实际年龄和既往疾病或状况等人口统计学因素后，新冠病毒病大流行开始前10 - 14年的加速衰老与检测呈阳性相关（每5年加速OR = 1.15，95%CI：1.08至1.21，p = 3.2×10），以及与检测确诊的新冠病毒病导致的全因死亡率相关（每5年加速OR = 1.25，95%CI：1.09至1.44，p = 0.002）。相应的曲线下面积分别为0.669和0.803。由PhenoAge所反映的生物学衰老，比实际年龄更能预测新冠病毒病的严重程度，并且可能为风险分层举措提供信息，同时还能阐明可能的潜在机制，特别是那些与炎症衰老相关的机制。
