There is growing scientific interest to develop scalable biological measures that capture mitochondrial (dys)function. Mitochondria have their own genome, the mitochondrial DNA (mtDNA). It has been proposed that the number of mtDNA copies per cell (mtDNA copy number; mtDNAcn) reflects mitochondrial health. The common availability of stored DNA material or existing DNA sequencing data, especially from blood and other easy-to-collect samples, has made its quantification a popular approach in clinical and epidemiological studies. However, the interpretation of mtDNAcn is not univocal, and either a reduction or elevation in mtDNAcn can indicate dysfunction. The major determinants of blood-derived mtDNAcn are the heterogeneous cell type composition of leukocytes and platelet abundance, which can change with time of day, aging, and with disease. Hematopoiesis is a likely driver of blood mtDNAcn. Here we discuss the rationale and available methods to quantify mtDNAcn, the influence of blood cell type variations, and consider important gaps in knowledge that need to be resolved to maximize the scientific value around the investigation of blood mtDNAcn.

人们越来越有兴趣开发可扩展的生物措施来捕获线粒体（功能障碍）。线粒体有自己的基因组，即线粒体 DNA (mtDNA)。有人提出，每个细胞的线粒体DNA拷贝数（mtDNA拷贝数；mtDNAcn）反映了线粒体的健康状况。存储的 DNA 材料或现有的 DNA 测序数据（尤其是来自血液和其他易于收集的样本）的普遍可用性，使其定量成为临床和流行病学研究中的流行方法。然而，mtDNAcn 的解释并不明确，mtDNAcn 的减少或升高都可能表明功能障碍。血液来源 mtDNAcn 的主要决定因素是白细胞和血小板丰度的异质细胞类型组成，它们会随着时间、衰老和疾病而变化。造血作用可能是血液 mtDNAcn 的驱动因素。在这里，我们讨论量化 mtDNAcn、血细胞类型变异的影响的基本原理和可用方法，并考虑需要解决的重要知识空白，以最大限度地提高血液 mtDNAcn 研究的科学价值。