A clinically meaningful metric of immune age derived from high-dimensional longitudinal monitoring

Abstract

Immune responses generally decline with age. However, the dynamics of this process at the individual level have not been characterized, hindering quantification of an individual’s immune age. Here, we use multiple ‘omics’ technologies to capture population- and individual-level changes in the human immune system of 135 healthy adult individuals of different ages sampled longitudinally over a nine-year period. We observed high inter-individual variability in the rates of change of cellular frequencies that was dictated by their baseline values, allowing identification of steady-state levels toward which a cell subset converged and the ordered convergence of multiple cell subsets toward an older adult homeostasis. These data form a highdimensional trajectory of immune aging (IMM-AGE) that describes a person’s immune status better than chronological age. We show that the IMM-AGE score predicted all-cause mortality beyond well-established risk factors in the Framingham Heart Study, establishing its potential use in clinics for identification of patients at risk. Reporting Summary. Further information on experimental design is available in the Nature Research Reporting Summary linked to this article.

Vaccine-induced ICOS+CD38+ cTfh are sensitive biosensors of age-related changes in inflammatory pathways

“…We found strong enrichment of the signatures of youth and aging in the young and elderly adults, respectively (Figure 6A). The signature of youth had gene ontology terms for RNA metabolism whereas the signature of aging had terms for fatty acid metabolism and cytoskeletal regulation (Supplemental Figure 6B), in agreement with other signatures of aging (28).To further validate these signatures, we identified several published studies (13,(50)(51)(52) that generated whole-blood transcriptional profiles on adults under age 40 or over age 65 ( Supplemental Table 8). From these data, we performed differential expression analysis of young compared to elderly in multiple geographically distinct studies and again found robust enrichment for these signatures in the external datasets ( Figure 6B, Supplemental Figure 6C).…”

“…To further validate these signatures, we identified several published studies (13,(50)(51)(52) that generated whole-blood transcriptional profiles on adults under age 40 or over age 65 ( Supplemental Table 8). From these data, we performed differential expression analysis of young compared to elderly in multiple geographically distinct studies and again found robust enrichment for these signatures in the external datasets ( Figure 6B, Supplemental Figure 6C).…”

An Inflammatory Clock Predicts Multi-morbidity, Immunosenescence and Cardiovascular Aging in Humans

“…From these observations, it has been postulated that inflammation plays a critical role in regulating physiological aging (Franceschi and Campisi, 2014;Furman et al, 2017b). Furthermore, the well-established nine hallmarks of aging (Lopez-Otin et al, 2013); (1) genomic instability, (2) shortening telomere length, (3) epigenetic modifications, (4) loss of proteostasis, (5) deregulated nutrient sensing, (6) mitochondrial dysfunction, (7) cellular senescence, (8) stem cell exhaustion, and (9) altered intracellular communication, have all been shown to be caused, at least in part, by sustained systemic inflammation (Cavadas et al, 2016;Efeyan et al, 2015;Grivennikov et al, 2010;Hunter et al, 2007;Jurk et al, 2014;Lasry and Ben-Neriah, 2015;Nathan and Cunningham-Bussel, 2013;Oh et al, 2014;Thevaranjan et al, 2017;Alpert et al, 2019).…”

Systems-level immunomonitoring using self-sampled capillary blood

“…Finally, by longitudinal monitoring of healthy individuals we are learning how newborn immune systems are shaped early in life 9 , and how immunological changes associated with aging manifest itself and affect disease risks in the elderly 10 .…”