Multidimensional single-cell analysis of human peripheral blood reveals characteristic features of the immune system landscape in aging and frailty

Luo, Oscar Junhong; Wen, Lu; Zhu, Guodong; Ren, Zhiyao; Xu, Yuewen; Xiao, Chanchan; Zhang, Hongyi; Cai, Junxiang; Luo, Zhiping; Gao, Lijuan; Su, Jun; Tang, Lei; Guo, Wei; Su, Huanxing; Zhang, Zhang-Jin; Fang, Evandro Fei; Ruan, Yijun; Leng, Sean X.; Ju, Zhenyu; Lou, Huiling; Gao, Junling; Peng, Nan; Chen, Jie; Bao, Zhijun; Liu, Feng; Chen, Guobing

doi:10.1038/s43587-022-00198-9

Cited by 71 publications

(59 citation statements)

References 49 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To see if this trend continued to earlier points in human development, we next asked whether naive CD4 T cells in cord blood from newborn infants also demonstrated the same skew in naive CD4 T cell gene expression as seen in pediatric subjects. Utilizing the same approach as described above on two publicly available scRNA-seq datasets from cord blood ( 21 , 22 ), we found that cord blood naive CD4 T cells had expression patterns similar to children, with high expression of SOX4 and TOX and conversely low expression of CPQ and STAT4. ( Figure 7C ) To verify that this transcription signature is specific to naive CD4 T cells developing early in life, we then performed RT-qPCR on bulk naive CD4 T cells from a new cohort of cord blood (n=7) and older adult peripheral blood (n=6, >60 yrs) using fluorescence-assisted cell sorting (FACS) based on the following protein expression pattern: CD4 + CD8 − CD45RA + CCR7 + CD27 + CD95 − .…”

Section: Resultsmentioning

confidence: 99%

“…(C) Average expression of cell state marker genes in naive CD4 T cells from scRNA-seq datasets, including an external cord blood dataset. ( 21 , 22 ) (D) Gene expression of SOX4, TOX, CPQ and STAT4 in bulk sorted naive CD4 T cells (CD3+CD4+CD8-CD45RA+CCR7+CD27+CD95-) from newborn cord blood (n = 7 donors) and older adult peripheral blood (n = 6 donors) as determined by qRT-PCR. Mann-Whitney test.…”

Section: Resultsmentioning

confidence: 99%

“…External cord blood scRNA-seq datasets are from GEO database (IDs: GSE157007 and GSE165193). ( 21 , 22 )…”

Section: Data and Materials Availabilitymentioning

confidence: 99%

See 2 more Smart Citations

Distinct Heterogeneity in the Naive T cell Compartments of Children and Adults

Gustafson

Thomson

et al. 2022

Preprint

View full text Add to dashboard Cite

The naive T cell compartment undergoes multiple changes across age that associate with altered susceptibility to infection and autoimmunity. In addition to the acquisition of naive-like memory T cell subsets, mouse studies describe substantial molecular reprogramming of the naive compartment in adults compared with adolescents. However, these alterations are not well delineated in human aging. Using a new trimodal single cell technology (TEA-seq), we discovered that the composition and transcriptional and epigenetic programming of the naive T cell compartment in children (11-13 yrs) is distinct from that of older adults (55-65 yrs). Naive CD4 T cells, previously considered relatively resistant to aging, exhibited far more pronounced molecular reprogramming than naive CD8 T cells, in which alterations are preferentially driven by shifts in naive-like memory subsets. These data reveal the complex nature of the naive T cell compartment that may contribute to differential immune responses across the spectrum of human age.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Distinct Heterogeneity in the Naive T cell Compartments of Children and Adults

Gustafson

Thomson

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…The subclustering was performed via Seurat with top 13 principal components and a resolution of 0.4. To identify cell types in sample datasets, we used sets of marker genes for each of those cell types and annotated each cell type based on their average expression and expression ratio as previously described ( 11 , 12 ).…”

Section: Methodsmentioning

confidence: 99%

Alzheimer’s disease alters the transcriptomic profile of natural killer cells at single-cell resolution

Liu

Zhang

et al. 2022

Front. Immunol.

View full text Add to dashboard Cite

Alzheimer’s disease (AD) is the most common dementia without an effective cure at least partially due to incomplete understanding of the disease. Inflammation has emerged as a central player in the onset and progression of AD. As innate lymphoid cells, natural killer (NK) cells orchestrate the initiation and evolution of inflammatory responses. Yet, the transcriptomic features of NK cells in AD remain poorly understood. We assessed the diversity of NK cells using web-based single-cell RNA sequencing data of blood NK cells from patients with AD and control subjects and flow cytometry. We identified a contraction of NK cell compartment in AD, accompanied by a reduction of cytotoxicity. Unbiased clustering revealed four subsets of NK cells in AD, i.e., CD56bright NK cells, CD56dim effector NK cells, adaptive NK cells, and a unique NK cell subset that is expanded and characterized by upregulation of CX3CR1, TBX21, MYOM2, DUSP1, and ZFP36L2, and negatively correlated with cognitive function in AD patients. Pseudo-temporal analysis revealed that this unique NK cell subset was at a late stage of NK cell development and enriched with transcription factors TBX21, NFATC2, and SMAD3. Together, our study identified a distinct NK cell subset and its potential involvement in AD.

show abstract

“…In the latest study recently published in Nature Aging, Luo and colleagues performed a comprehensive single-cell transcriptomic and TCR repertoire analysis, identifying gene expression signatures and functional characteristics of immune cell subsets along the whole spectrum of the aging process, from neonates (using cord blood) and young adults as controls to two groups of older adults who either appeared to be healthy (“healthy aging”) or who were frail (“frailty”) with similar chronological age (85.8 ± 11.1 years vs 88 ± 5.8 years, respectively) ( Fig. 1 ) [ 8 ].…”

mentioning

confidence: 99%