Cited by 390Immune cells in cancerImmune Response and InflammationAtherosclerosis and Cardiovascular Diseases

The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.

Age-dependent alterations of monocyte subsets and monocyte-related chemokine pathways in healthy adults

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Abstract

Background: Recent experimental approaches have unraveled essential migratory and functional differences of monocyte subpopulations in mice. In order to possibly translate these findings into human physiology and pathophysiology, human monocyte subsets need to be carefully revisited in health and disease. In analogy to murine studies, we hypothesized that human monocyte subsets dynamically change during ageing, potentially influencing their functionality and contributing to immunosenescence. Results: Circulating monocyte subsets, surface marker and chemokine receptor expression were analyzed in 181 healthy volunteers (median age 42, range 18-88). Unlike the unaffected total leukocyte or total monocyte counts, non-classical CD14 + CD16 + monocytes significantly increased with age, but displayed reduced HLA-DR and CX 3 CR1 surface expression in the elderly. Classical CD14 ++ CD16 - monocyte counts did not vary dependent on age. Serum MCP-1 (CCL2), but not MIP1α (CCL3), MIP1β (CCL4) or fractalkine (CX 3 CL1) concentrations increased with age. Monocyte-derived macrophages from old or young individuals did not differ with respect to cytokine release in vitro at steady state or upon LPS stimulation. Conclusions: Our study demonstrates dynamic changes of circulating monocytes during ageing in humans. The expansion of the non-classical CD14 + CD16 + subtype, alterations of surface protein and chemokine receptor expression as well as circulating monocyte-related chemokines possibly contribute to the preserved functionality of the monocyte pool throughout adulthood.

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Crossref · 10.1186/1471-2172-11-30

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Figures

Figure 1 Age-dependent changes of circulating leukocytes. Box plots display absolute numbers of circulating total leukocytes (A), neutrophils (B), monocytes (C), lymphocytes (D) and lymphocyte subsets (E) in 109/L for the different groups of young (<30 years, n = 51), middle-aged (30-50 years, n = 70) and old (>50 years, n = 60) healthy volunteers. The bold black line indicates the median per group, the box represents 50% of the values, and horizontal lines show minimum and maximum values of the calculated non-outlier values; open circles indicate outlier values. Significant differences (Kruskal-Wallis and U-test) are marked by *p < 0.05.
Figure 1 Age-dependent changes of circulating leukocytes. Box plots display absolute numbers of circulating total leukocytes (A), neutrophils (B), monocytes (C), lymphocytes (D) and lymphocyte subsets (E) in 109/L for the different groups of young (<30 years, n = 51), middle-aged (30-50 years, n = 70) and old (>50 years, n = 60) healthy volunteers. The bold black line indicates the median per group, the box represents 50% of the values, and horizontal lines show minimum and maximum values of the calculated non-outlier values; open circles indicate outlier values. Significant differences (Kruskal-Wallis and U-test) are marked by *p < 0.05.CC BY · PubMed Central
Figure 2 Age-dependent changes of circulating monocyte subsets. (A) Representative FACS plots display an increase of CD14+CD16+ monocytes (grey gate) in comparison to classical CD14++CD16- monocytes (black gate) among freshly isolated PBMC from old (right plot, 51 years-old male) versus young (left plot, 24 years-old female) volunteers. (B) Box plots display absolute numbers of circulating CD14++CD16- monocytes (left), CD14+CD16+ monocytes (middle) and the relative percentage of CD14+CD16+ from total monocytes (right) for the different groups of young (<30 years, n = 51), middle-aged (30-50 years, n = 70) and old (>50 years, n = 60) healthy volunteers. The bold black line indicates the median per group, the box represents 50% of the values, and horizontal lines show minimum and maximum values of the calculated non-outlier values; open circles indicate outlier values. Significant differences (Kruskal-Wallis and U-test) are marked by *p < 0.05, **p < 0.01 and ***p < 0.0015.
Figure 2 Age-dependent changes of circulating monocyte subsets. (A) Representative FACS plots display an increase of CD14+CD16+ monocytes (grey gate) in comparison to classical CD14++CD16- monocytes (black gate) among freshly isolated PBMC from old (right plot, 51 years-old male) versus young (left plot, 24 years-old female) volunteers. (B) Box plots display absolute numbers of circulating CD14++CD16- monocytes (left), CD14+CD16+ monocytes (middle) and the relative percentage of CD14+CD16+ from total monocytes (right) for the different groups of young (<30 years, n = 51), middle-aged (30-50 years, n = 70) and old (>50 years, n = 60) healthy volunteers. The bold black line indicates the median per group, the box represents 50% of the values, and horizontal lines show minimum and maximum values of the calculated non-outlier values; open circles indicate outlier values. Significant differences (Kruskal-Wallis and U-test) are marked by *p < 0.05, **p < 0.01 and ***p < 0.0015.CC BY · PubMed Central
Figure 3 Age-dependent changes of HLA-DR and chemokine receptor expression on monocyte subsets. (A) HLA-DR expression was analyzed by FACS on monocyte subsets (representative histogram of a 52-years old male is shown). Box plots demonstrate alterations of HLA-DR expression on both subsets using the ratio of HLA-DR between CD14+CD16+ and CD14++CD16- monocytes for the different groups of young (<30 years, n = 37), middle-aged (30-50 years, n = 50) and old (>50 years, n = 43) healthy volunteers. *p < 0.05. (B) Chemokine receptor expression was studied by FACS on both circulating monocyte subsets. Representative histograms (from a 65-years old male) display that CD14+CD16+ monocytes express higher levels of CX3CR1, whereas CCR2 is primarily detected on classical CD14++CD16- monocytes. (C) Bar graphs depict changes in chemokine receptor expression (quantified as median fluorescence intensity minus "fluorescence minus one", MFI-FMO) for both monocyte subsets for the different groups of young (<30 years, n = 21), middle-aged (30-50 years, n = 22) and old (>50 years, n = 19) healthy volunteers. *p < 0.05.
Figure 3 Age-dependent changes of HLA-DR and chemokine receptor expression on monocyte subsets. (A) HLA-DR expression was analyzed by FACS on monocyte subsets (representative histogram of a 52-years old male is shown). Box plots demonstrate alterations of HLA-DR expression on both subsets using the ratio of HLA-DR between CD14+CD16+ and CD14++CD16- monocytes for the different groups of young (<30 years, n = 37), middle-aged (30-50 years, n = 50) and old (>50 years, n = 43) healthy volunteers. *p < 0.05. (B) Chemokine receptor expression was studied by FACS on both circulating monocyte subsets. Representative histograms (from a 65-years old male) display that CD14+CD16+ monocytes express higher levels of CX3CR1, whereas CCR2 is primarily detected on classical CD14++CD16- monocytes. (C) Bar graphs depict changes in chemokine receptor expression (quantified as median fluorescence intensity minus "fluorescence minus one", MFI-FMO) for both monocyte subsets for the different groups of young (<30 years, n = 21), middle-aged (30-50 years, n = 22) and old (>50 years, n = 19) healthy volunteers. *p < 0.05.CC BY · PubMed Central
Figure 4 Age-dependent changes of circulating monocyte-related chemokine levels. Box plots display serum concentrations of the chemokines MCP-1 (A), MIP1α (D), MIP1β (E) and fractalkine (F) for the different groups of young (<30 years, n = 51), middle-aged (30-50 years, n = 70) and old (>50 years, n = 60) healthy volunteers. The bold black line indicates the median per group, the box represents 50% of the values, and horizontal lines show minimum and maximum values of the calculated non-outlier values; open circles indicate outlier values. Significant differences (Kruskal-Wallis and U-test) are marked by ***p < 0.0015. (B+C) MCP1 serum concentrations correlate with the age (r = 0.266, p = 0.001) and the body-mass index (BMI, r = 0.430, p = 0.013) in healthy volunteers (Spearman rank correlation test).
Figure 4 Age-dependent changes of circulating monocyte-related chemokine levels. Box plots display serum concentrations of the chemokines MCP-1 (A), MIP1α (D), MIP1β (E) and fractalkine (F) for the different groups of young (<30 years, n = 51), middle-aged (30-50 years, n = 70) and old (>50 years, n = 60) healthy volunteers. The bold black line indicates the median per group, the box represents 50% of the values, and horizontal lines show minimum and maximum values of the calculated non-outlier values; open circles indicate outlier values. Significant differences (Kruskal-Wallis and U-test) are marked by ***p < 0.0015. (B+C) MCP1 serum concentrations correlate with the age (r = 0.266, p = 0.001) and the body-mass index (BMI, r = 0.430, p = 0.013) in healthy volunteers (Spearman rank correlation test).CC BY · PubMed Central
Figure 5 Functional properties of monocyte-derived macrophages from young and old volunteers. Macrophages derived from freshly isolated PBMC from n = 12 volunteers aged <30 years (<30) and from n = 10 volunteers aged >30 years (>30) were cultured in medium containing autologous serum for 24 h and then stimulated with 1 μg/ml LPS for additional 24 h or left untreated. (A) Macrophages display an activated, round-shaped morphology after LPS stimulation, but no overt morphological differences were detected between macrophages from young or old adults. (B) Bar graphs show mean cytokine and chemokine levels (in pg/mL) in the supernatant at day 2, error bars represent SEM.
Figure 5 Functional properties of monocyte-derived macrophages from young and old volunteers. Macrophages derived from freshly isolated PBMC from n = 12 volunteers aged <30 years (<30) and from n = 10 volunteers aged >30 years (>30) were cultured in medium containing autologous serum for 24 h and then stimulated with 1 μg/ml LPS for additional 24 h or left untreated. (A) Macrophages display an activated, round-shaped morphology after LPS stimulation, but no overt morphological differences were detected between macrophages from young or old adults. (B) Bar graphs show mean cytokine and chemokine levels (in pg/mL) in the supernatant at day 2, error bars represent SEM.CC BY · PubMed Central

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Metadata

Authors
Seidler, S., Zimmermann, H. W., Bartneck, M., Trautwein, C., & Tacke, F.
Affiliations
Universitätsklinikum Aachen (DE)
Corresponding author
Tacke, Frank
Venue
BMC Immunology
Published
2010-06-21
Volume
11
Issue
1
Pages
30-30
ISSN
1471-2172 (ISSN-L)
OpenAlex
W2058743791
Cited by
390
References
35
Citations by year
2026: 17 · 2025: 23 · 2024: 32 · 2023: 32 · 2022: 30 · 2021: 40 · 2020: 33 · 2019: 27 · 2018: 21 · 2017: 17 · 2016: 22 · 2015: 26 · 2014: 20 · 2013: 22 · 2012: 16
FWCI
6.45
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • BMC Immunology (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • RWTH Publications (RWTH Aachen) (submittedVersion, cc-by)
  • RWTH Publications (RWTH Aachen)
Funders
  • Deutsche Forschungsgemeinschaft (GRK 1035, DFG Ta434/2–1, SFB‐TRR57, Ta434/2-1, DFG: SFB/TRR57)
  • RWTH Aachen University
Topics
  • Life Sciences › Immunology and Microbiology › Immunology › Immune cells in cancer
  • Life Sciences › Immunology and Microbiology › Immunology › Immune Response and Inflammation
  • Life Sciences › Immunology and Microbiology › Immunology › Atherosclerosis and Cardiovascular Diseases
Keywords
monocyte subsets, aging, immunosenescence, CD14+CD16+ monocytes, classical monocytes, CX3CR1, HLA-DR, chemokine receptors, MCP-1, monocyte-derived macrophages, cytokine production, lipopolysaccharide stimulation, healthy adults
MeSH terms
Adolescent, Adult, Aged, Aged, 80 and over, Aging, Cell Movement, Female, Health, HLA-DR Antigens, Humans, Macrophages, Male, Middle Aged, Monocytes, Cohort Studies, Signal Transduction, Receptors, IgG, Chemokines, Chemokine CCL2, Lipopolysaccharide Receptors, Receptors, Chemokine, Young Adult

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