Nature aging最新文献

The aging of hematopoietic stem cells (HSCs) substantially alters their characteristics. Mitochondria, essential for cellular metabolism, play a crucial role, and their dysfunction is a hallmark of aging-induced changes. The impact of mitochondrial mass on aged HSCs remains incompletely understood. Here we demonstrate that HSCs with high mitochondrial mass during aging are not merely cells that have accumulated damaged mitochondria and become exhausted. In addition, these HSCs retain a high regenerative capacity and remain in the aging bone marrow. Furthermore, we identified GPR183 as a distinct marker characterizing aged HSCs through single-cell analysis. HSCs marked by GPR183 were also enriched in aged HSCs with high mitochondrial mass, possessing a high capacity of self-renewal. These insights deepen understanding of HSC aging and provide additional perspectives on the assessment of aged HSCs, underscoring the importance of mitochondrial dynamics in aging.

Aging affects human immune system functionality, increasing susceptibility to immune-mediated diseases. While gene expression programs accurately reflect immune function, their relationship with biological immune aging and health status remains unclear. Here we developed robust, cell-type-specific aging clocks (sc-ImmuAging) for the myeloid and lymphoid immune cell populations in circulation within peripheral blood mononuclear cells, using single-cell RNA-sequencing data from 1,081 healthy individuals aged from 18 to 97 years. Application of sc-ImmuAging to transcriptome data of patients with COVID-19 revealed notable age acceleration in monocytes, which decreased during recovery. Furthermore, inter-individual variations in immune aging induced by vaccination were identified, with individuals exhibiting elevated baseline interferon response genes showing age rejuvenation in CD8⁺ T cells after BCG vaccination. sc-ImmuAging provides a powerful tool for decoding immune aging dynamics, offering insights into age-related immune alterations and potential interventions to promote healthy aging.

Cancer is an age-related disease, but the interplay between cancer and aging is complex and their shared molecular drivers are deeply intertwined. This Review provides an overview of how different biological pathways affect cancer and aging, leveraging evidence mainly derived from animal studies. We discuss how genome maintenance and accumulation of DNA mutations affect tumorigenesis and tissue homeostasis during aging. We describe how age-related telomere dysfunction and cellular senescence intricately modulate tumor development through mechanisms involving genomic instability and inflammation. We examine how an aged immune system and chronic inflammation shape tumor immunosurveillance, fueling DNA damage and cellular senescence. Finally, as animal models are important to untangling the relative contributions of these aging-modulated pathways to cancer progression and to test interventions, we discuss some of the limitations of physiological and accelerated aging models, aiming to improve experimental designs and enhance translation.

Testicular aging is associated with declining reproductive health, but the molecular mechanisms are unclear. Here we generate a dataset of 214,369 single-cell transcriptomes from testicular cells of 35 individuals aged 21-69, offering a resource for studying testicular aging and physiology. Machine learning analysis reveals a stronger aging response in somatic cells compared to germ cells. Two waves of aging-related changes are identified: the first in peritubular cells of donors in their 30s, marked by increased basement membrane thickness, indicating a priming state for aging. In their 50s, testicular cells exhibit functional changes, including altered steroid metabolism in Leydig cells and immune responses in macrophages. Further analyses reveal the impact of body mass index on spermatogenic capacity as age progresses, particularly after age 45. Altogether, our findings illuminate molecular alterations during testis aging and their relationship with body mass index, providing a foundation for future research and offering potential diagnostic markers and therapeutic targets.

Blood-borne factors are essential to maintain neuronal synaptic plasticity and cognitive resilience throughout life. One such factor is osteocalcin (OCN), a hormone produced by osteoblasts that influences multiple physiological processes, including hippocampal neuronal homeostasis. However, the mechanism through which this blood-borne factor communicates with neurons remains unclear. Here we show the importance of a core primary cilium (PC) protein-autophagy axis in mediating the effects of OCN. We found that the OCN receptor GPR158 is present at the PC of hippocampal neurons and mediates the regulation of autophagy machinery by OCN. During aging, autophagy and PC core proteins are reduced in neurons, and restoring their levels is sufficient to improve cognitive impairments in aged mice. Mechanistically, the induction of this axis by OCN is dependent on the PC-dependent cAMP response element-binding protein signaling pathway. Altogether, this study demonstrates that the PC-autophagy axis is a gateway to mediate communication between blood-borne factors and neurons, and it advances understanding of the mechanisms involved in age-related cognitive decline.

The early pathophysiology of Parkinson's disease (PD) is poorly understood. We analyzed 2,920 Olink-measured plasma proteins in 51,804 UK Biobank participants, identifying 859 incident PD cases after 14.45 years. We found 38 PD-related proteins, with six of the top ten validated in the Parkinson's Progression Markers Initiative (PPMI) cohort. ITGAV, HNMT and ITGAM showed consistent significant association (hazard ratio: 0.11-0.57, P = 6.90 × 10^-24 to 2.10 × 10^-11). Lipid metabolism dysfunction was evident 15 years before PD onset, and levels of BAG3, HPGDS, ITGAV and PEPD continuously decreased before diagnosis. These proteins were linked to prodromal symptoms and brain measures. Mendelian randomization suggested ITGAM and EGFR as potential causes of PD. A predictive model using machine learning combined the top 16 proteins and demographics, achieving high accuracy for 5-year (area under the curve (AUC) = 0.887) and over-5-year PD prediction (AUC = 0.816), outperforming demographic-only models. It was externally validated in PPMI (AUC = 0.802). Our findings reveal early peripheral pathophysiological changes in PD crucial for developing early biomarkers and precision therapies.