Undulating changes in human plasma proteome across lifespan are linked to disease

Abstract

<jats:p>Aging is the predominant risk factor for numerous chronic diseases that limit healthspan. Mechanisms of aging are thus increasingly recognized as therapeutic targets. Blood from young mice reverses aspects of aging and disease across multiple tissues, pointing to the intriguing possibility that age-related molecular changes in blood can provide novel insight into disease biology. We measured 2,925 plasma proteins from 4,331 young adults to nonagenarians and developed a novel bioinformatics approach which uncovered profound non-linear alterations in the human plasma proteome with age. Waves of changes in the proteome in the fourth, seventh, and eighth decades of life reflected distinct biological pathways, and revealed differential associations with the genome and proteome of age-related diseases and phenotypic traits. This new approach to the study of aging led to the identification of unexpected signatures and pathways of aging and disease and offers potential pathways for aging interventions.</jats:p>

An inflammatory aging clock (iAge) based on deep learning tracks multimorbidity, immunosenescence, frailty and cardiovascular aging

“…Similar to our previous findings on the cytokine response score for diastolic dysfunction and atherosclerotic burden 28 , our inflammatory clock metric specifically hones in on the crucial role that the immune system and systemic chronic inflammation play in the accumulation of diseases of aging, with a focus on cardiovascular aging. Unlike other metrics of 'biological' age which do not offer a clinically relevant metric 92 we demonstrate that iAge predicts multimorbidity, and therefore can be used as a biological surrogate of age-related health vs. disease. iAge is directly associated with multiple disease phenotypes including cardiovascular aging, frailty, immune decline and exceptional longevity.…”

A catalogue of omics biological ageing clocks reveals substantial commonality and associations with disease risk

“…DNAme's verification as a meaningful BA measure, rather than a mere statistical artefact, was confirmed when DNAme OCAA as calculated by Horvath's clock was shown to be associated with all-cause mortality 7 . Ageing clocks trained on chronAge have since been constructed using DNA methylation 5,6,8 , telomere length 9 , facial morphology 10 , neuro-imaging data [11][12][13][14] , metabolomics 15,16 , glycomics 17 , proteomics [18][19][20] and immune cell counts 21 . There has however, been limited comparison of the performance, for example accuracy and correlation, of different omics ageing clocks, particularly in the same set of individuals.…”

Crosstalk between the aging intestinal microflora and the brain in ischemic stroke

“…The plasticity of brain immune cells influences the homeostasis of brain parenchyma as well as diseases and is strongly dependent on the microenvironment and systemic factors. Blood metabolites and cytokines have been shown to be altered by intestinal dysbiosis leading to dysregulation of the peripheral immune system (Arpaia et al, 2013;Bachem et al, 2019;Lehallier et al, 2019). Brain immunity and central nervous system inflammation are also indirectly altered by dysbiosis via signaling metabolites (neurotransmitters) produced by the intestinal microflora (Table 1; Erny et al, 2015;Dinan and Cryan, 2017;Ma et al, 2019).…”