Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland.
Laboratory of Neurobiology, Centro Investigación Príncipe Felipe, Valencia, Spain.
Cell Rep Methods. 2022 Aug 22;2(8):100269. doi: 10.1016/j.crmeth.2022.100269.
B and T cell receptor (immune) repertoires can represent an individual's immune history. While current repertoire analysis methods aim to discriminate between health and disease states, they are typically based on only a limited number of parameters. Here, we introduce immuneREF: a quantitative multidimensional measure of adaptive immune repertoire (and transcriptome) similarity that allows interpretation of immune repertoire variation by relying on both repertoire features and cross-referencing of simulated and experimental datasets. To quantify immune repertoire similarity landscapes across health and disease, we applied immuneREF to >2,400 datasets from individuals with varying immune states (healthy, [autoimmune] disease, and infection). We discovered, in contrast to the current paradigm, that blood-derived immune repertoires of healthy and diseased individuals are highly similar for certain immune states, suggesting that repertoire changes to immune perturbations are less pronounced than previously thought. In conclusion, immuneREF enables the population-wide study of adaptive immune response similarity across immune states.
B 和 T 细胞受体（免疫）库可以代表个体的免疫史。虽然当前的库分析方法旨在区分健康和疾病状态，但它们通常基于数量有限的参数。在这里，我们引入了 immuneREF：一种适应性免疫库（和转录组）相似性的定量多维度量标准，它通过依赖于库特征和模拟数据集与实验数据集的交叉引用来解释免疫库的变化。为了量化健康和疾病状态下的免疫库相似性景观，我们将 immuneREF 应用于来自具有不同免疫状态（健康、[自身免疫]疾病和感染）的个体的 >2400 个数据集。我们发现，与当前的范式相反，对于某些免疫状态，健康和患病个体的血液衍生免疫库非常相似，这表明对免疫扰动的库变化不如以前想象的那么明显。总之，immuneREF 能够在整个人群中研究免疫状态下适应性免疫反应的相似性。
