Kuiper Lieke M, Mens Michelle M J, Wu Julia W, Goudsmit Jaap, Ma Yuan, Liang Liming, Hofman Albert, Voortman Trudy, Ikram M Arfan, van Rooij Jeroen G J, van Meurs Joyce B J, Ghanbari Mohsen
Department of Internal Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands.
Center for Prevention, Lifestyle and Health, National Institute for Public Health and Environment (RIVM), Bilthoven, the Netherlands.
Genome Med. 2025 Jun 25;17(1):70. doi: 10.1186/s13073-025-01437-5.
MicroRNAs are small non-coding RNAs that regulate gene expression post-transcriptionally and show differential expression in various tissues with aging phenotypes. Detectable in circulation, extracellular microRNAs reflect (patho)physiological processes and hold promise as biomarkers for healthy aging and age-related diseases. This study aimed to explore plasma extracellular microRNAs as a biological aging indicator and their associations with health outcomes using population-level data.
We quantified plasma expression levels of 2083 extracellular microRNAs using targeted RNA-sequencing in 2684 participants from the population-based Rotterdam Study cohort. The training and test sets included 1930 participants from the advanced-aged initial and second subcohort (RS-I/RS-II; median age: 70.6), while the validation set comprised 754 participants from the middle-aged fourth subcohort (RS-IV; median age: 53.5). Based on 591 microRNAs well-expressed in plasma, we examined differential expression of microRNAs with chronological age, PhenoAge-a composite score of age and nine multi-system blood biomarkers-the frailty index, and mortality. Next, elastic net models were employed to construct composite microRNA-based aging biomarkers predicting chronological age (mirAge), PhenoAge (mirPA), frailty index (mirFI), and mortality (mirMort). The association of these aging biomarkers with different age-related health outcomes was assessed using Cox Proportional Hazard, linear regression, and logistic regression models in the test and validation sets.
We identified 188 microRNAs differentially expressed with chronological age within the RS-I/RS-II advanced-aged population (n = 1158, n = 772), of which 177 microRNAs (94.1%) were replicated in the middle-aged RS-IV subcohort (n = 754). Moreover, 227 miRNAs showed robust associations with PhenoAge, 61 with FI, and 16 with 10-year mortality independent of chronological age. Subsequently, we constructed four plasma microRNA-based aging biomarkers: mirAge with 108, mirPA with 153, mirFI with 81, and mirMort with 50 miRNAs. Elevated scores on these microRNA-based aging biomarkers were associated with unfavorable health outcomes, including lower subjective physical functioning and self-reported health and increased mortality and frailty risk, but not with first- or multi-morbidity. Overall, larger effect estimates were observed for mirPA, mirFI, and mirMort compared to mirAge.
This study describes distinct plasma microRNA-aging signatures and introduces four microRNA-based aging biomarkers with the potential to identify accelerated aging and age-related decline, providing insights into the intricate process of human aging.
微小RNA是一类小的非编码RNA，可在转录后调节基因表达，并在具有衰老表型的各种组织中呈现差异表达。细胞外微小RNA可在循环中检测到，反映（病理）生理过程，有望成为健康衰老和年龄相关疾病的生物标志物。本研究旨在利用人群水平的数据，探索血浆细胞外微小RNA作为生物衰老指标及其与健康结局的关联。
我们在基于人群的鹿特丹研究队列的2684名参与者中，使用靶向RNA测序对2083种细胞外微小RNA的血浆表达水平进行了定量。训练集和测试集包括来自高龄初始和第二个亚队列（RS-I/RS-II；中位年龄：70.6岁）的1930名参与者，而验证集包括来自中年第四个亚队列（RS-IV；中位年龄：53.5岁）的754名参与者。基于在血浆中表达良好的591种微小RNA，我们研究了微小RNA随实际年龄、PhenoAge（年龄与九种多系统血液生物标志物的综合评分）、衰弱指数和死亡率的差异表达。接下来，采用弹性网络模型构建基于微小RNA的综合衰老生物标志物，以预测实际年龄（mirAge）、PhenoAge（mirPA）、衰弱指数（mirFI）和死亡率（mirMort）。在测试集和验证集中，使用Cox比例风险模型、线性回归模型和逻辑回归模型评估这些衰老生物标志物与不同年龄相关健康结局的关联。
我们在RS-I/RS-II高龄人群（n = 1158，n = 772）中鉴定出188种随实际年龄差异表达的微小RNA，其中177种微小RNA（94.1%）在中年RS-IV亚队列（n = 754）中得到重复验证。此外，227种微小RNA与PhenoAge有显著关联，61种与衰弱指数有关，16种与10年死亡率有关，且不受实际年龄影响。随后，我们构建了四种基于血浆微小RNA的衰老生物标志物：mirAge包含108种微小RNA，mirPA包含153种，mirFI包含81种，mirMort包含50种。这些基于微小RNA的衰老生物标志物得分升高与不良健康结局相关，包括较低的主观身体功能和自我报告的健康状况，以及死亡率和衰弱风险增加，但与首发或多种疾病无关。总体而言，与mirAge相比，mirPA、mirFI和mirMort的效应估计值更大。
本研究描述了独特的血浆微小RNA衰老特征，并引入了四种基于微小RNA的衰老生物标志物，它们有可能识别加速衰老和与年龄相关的衰退，为人类衰老的复杂过程提供了见解。
