Lieke M Kuiper, Michelle M J Mens, Julia W Wu, Jaap Goudsmit, Yuan Ma, Liming Liang, Albert Hofman, Trudy Voortman, M Arfan Ikram, Jeroen G J van Rooij, Joyce B J van Meurs, Mohsen Ghanbari
{"title":"衰老的血浆microRNA特征及其与健康结果和死亡率的联系:一项基于人群的队列研究的发现","authors":"Lieke M Kuiper, Michelle M J Mens, Julia W Wu, Jaap Goudsmit, Yuan Ma, Liming Liang, Albert Hofman, Trudy Voortman, M Arfan Ikram, Jeroen G J van Rooij, Joyce B J van Meurs, Mohsen Ghanbari","doi":"10.1186/s13073-025-01437-5","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>We identified 188 microRNAs differentially expressed with chronological age within the RS-I/RS-II advanced-aged population (n<sub>training</sub> = 1158, n<sub>test</sub> = 772), of which 177 microRNAs (94.1%) were replicated in the middle-aged RS-IV subcohort (n<sub>validation</sub> = 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.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"70"},"PeriodicalIF":10.4000,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12188677/pdf/","citationCount":"0","resultStr":"{\"title\":\"Plasma microRNA signatures of aging and their links to health outcomes and mortality: findings from a population-based cohort study.\",\"authors\":\"Lieke M Kuiper, Michelle M J Mens, Julia W Wu, Jaap Goudsmit, Yuan Ma, Liming Liang, Albert Hofman, Trudy Voortman, M Arfan Ikram, Jeroen G J van Rooij, Joyce B J van Meurs, Mohsen Ghanbari\",\"doi\":\"10.1186/s13073-025-01437-5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>We identified 188 microRNAs differentially expressed with chronological age within the RS-I/RS-II advanced-aged population (n<sub>training</sub> = 1158, n<sub>test</sub> = 772), of which 177 microRNAs (94.1%) were replicated in the middle-aged RS-IV subcohort (n<sub>validation</sub> = 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.</p><p><strong>Conclusions: </strong>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.</p>\",\"PeriodicalId\":12645,\"journal\":{\"name\":\"Genome Medicine\",\"volume\":\"17 1\",\"pages\":\"70\"},\"PeriodicalIF\":10.4000,\"publicationDate\":\"2025-06-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12188677/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Genome Medicine\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1186/s13073-025-01437-5\",\"RegionNum\":1,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GENETICS & HEREDITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Genome Medicine","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1186/s13073-025-01437-5","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
Plasma microRNA signatures of aging and their links to health outcomes and mortality: findings from a population-based cohort study.
Background: 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.
Methods: 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.
Results: We identified 188 microRNAs differentially expressed with chronological age within the RS-I/RS-II advanced-aged population (ntraining = 1158, ntest = 772), of which 177 microRNAs (94.1%) were replicated in the middle-aged RS-IV subcohort (nvalidation = 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.
Conclusions: 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.
期刊介绍:
Genome Medicine is an open access journal that publishes outstanding research applying genetics, genomics, and multi-omics to understand, diagnose, and treat disease. Bridging basic science and clinical research, it covers areas such as cancer genomics, immuno-oncology, immunogenomics, infectious disease, microbiome, neurogenomics, systems medicine, clinical genomics, gene therapies, precision medicine, and clinical trials. The journal publishes original research, methods, software, and reviews to serve authors and promote broad interest and importance in the field.