Lifetime age-related changes in clinical laboratory results, aging clocks and mortality predictors in 2412 Golden Retrievers.

IF 8 1区 医学 Q1 CELL BIOLOGY
Aging Cell Pub Date : 2025-01-24 DOI:10.1111/acel.14438
Kevin Perez, Brenna Swafford, Julia Labadie, Alejandro Ocampo
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引用次数: 0

Abstract

In this study, we investigated age-related changes in clinical laboratory data and their association with mortality in dogs from the Golden Retriever Lifetime Study. By analyzing complete blood count (CBC) and biochemistry data from 2'412 Golden Retrievers over 16,678 visits, we observed significant changes during the first 2 years of life and throughout aging. Based on these observations, we developed a biological aging clock using a LASSO model to predict age based on blood markers, achieving an accuracy of R = 0.78. Although the biological age clock and pace of aging did not significantly improve mortality prediction, a model incorporating all blood biomarkers showed better predictive power for lifetime (C-index = 0.763) and 1-year mortality (AUC = 0.817). Our findings underscore the importance of comprehensive blood analysis for aging and mortality prediction in dogs and open the door for the development of novel methods to investigate aging in companion animals.

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来源期刊
Aging Cell
Aging Cell Biochemistry, Genetics and Molecular Biology-Cell Biology
自引率
2.60%
发文量
212
期刊介绍: Aging Cell is an Open Access journal that focuses on the core aspects of the biology of aging, encompassing the entire spectrum of geroscience. The journal's content is dedicated to publishing research that uncovers the mechanisms behind the aging process and explores the connections between aging and various age-related diseases. This journal aims to provide a comprehensive understanding of the biological underpinnings of aging and its implications for human health. The journal is widely recognized and its content is abstracted and indexed by numerous databases and services, which facilitates its accessibility and impact in the scientific community. These include: Academic Search (EBSCO Publishing) Academic Search Alumni Edition (EBSCO Publishing) Academic Search Premier (EBSCO Publishing) Biological Science Database (ProQuest) CAS: Chemical Abstracts Service (ACS) Embase (Elsevier) InfoTrac (GALE Cengage) Ingenta Select ISI Alerting Services Journal Citation Reports/Science Edition (Clarivate Analytics) MEDLINE/PubMed (NLM) Natural Science Collection (ProQuest) PubMed Dietary Supplement Subset (NLM) Science Citation Index Expanded (Clarivate Analytics) SciTech Premium Collection (ProQuest) Web of Science (Clarivate Analytics) Being indexed in these databases ensures that the research published in Aging Cell is discoverable by researchers, clinicians, and other professionals interested in the field of aging and its associated health issues. This broad coverage helps to disseminate the journal's findings and contributes to the advancement of knowledge in geroscience.
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