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Characterization of immune cells in psoriatic adipose tissue.

Rose S, Stansky E, Dagur PK, Samsel L, Weiner E, Jahanshad A, Doveikis J, Naik HB, Playford MP, McCoy JP, Mehta NN - J Transl Med (2014)

Bottom Line: Rarely have these populations been verified with confirmatory methodologies or functional studies.Further, both CD16+CD56(Lo) and CD16-CD56(Hi) NK cells were found to correlate inversely with body mass index.The relationship between the predominant CD16+CD56(Lo) NK cell population and body mass index persisted after adjusting for age, sex, diabetes, and tobacco use.

View Article: PubMed Central - PubMed

ABSTRACT

Background: Adipose tissue normally contains immune cells that regulate adipocyte function and contribute to metabolic disorders including obesity and diabetes mellitus. Psoriasis is associated with increased risk for metabolic disease, which may in part be due to adipose dysfunction, which has not been investigated in psoriasis. There is currently no standardized method for immunophenotyping human adipose tissue. In prior studies, characteristic phenotypic markers of immune cell populations identified in animal models or in other human tissues have been applied in a similar manner to human adipose tissue. Rarely have these populations been verified with confirmatory methodologies or functional studies. Thus, we performed a comprehensive phenotypic and functional analysis of immune cell populations in psoriatic adipose tissue.

Methods: Conventional and imaging flow cytometry were used to define immune cell populations in biopsy specimens of psoriatic adipose tissue (n = 30) including T cells, B cells, NK cells, NKT cells, neutrophils, and macrophages. Relationships between adipose immune cell types and body mass index were determined using Spearman regression analysis, and multivariate linear regression analysis was performed to adjust for cardiometabolic disease risk factors.

Results: These analyses revealed a wide range of cell surface receptors on adipose tissue macrophages, which may serve a dual purpose in immunity and metabolism. Further, both CD16+CD56(Lo) and CD16-CD56(Hi) NK cells were found to correlate inversely with body mass index. The relationship between the predominant CD16+CD56(Lo) NK cell population and body mass index persisted after adjusting for age, sex, diabetes, and tobacco use.

Conclusions: Together, these studies enhance our understanding of adipose immune cell phenotype and function, and demonstrate that examination of adipose tissue may provide greater insight into cardiometabolic pathophysiology in psoriasis.

No MeSH data available.


Related in: MedlinePlus

Nuclear morphologic analysis of CD16+ cell populations in adipose tissue confirms flow cytometric phenotypic analysis. Imaging flow cytometry of adipose tissue immune cells was performed as in Figure 3. After exclusion of non-nucleated cells and Hoechst saturating the camera, poorly focused cells, and debris/doublets, CD3-CD14- cells were gated on CD16+ cells. CD16+ cells (~30 cells for each group) were manually selected (Tagged) based on their nuclear morphology to distinguish mononuclear (Circular, panel A) from polymorphonuclear (Polymorph, panel B) cells. The Feature Finder wizard in IDEAS software was used to identify similar cells in the total CD16+ source population (Automated, panels C, E) and to exclude debris and unfocused cells (Automated, panel D). Circularity and Bright Detail Intensity of the Hoechst imagery were the 2 characteristics that best distinguished the manually selected Polymorph and Circular cells. A plot of these 2 parameters for the Tagged and Automated CD16+ populations is depicted. BF = brightfield microscopy, Hoec = Hoechst nuclear staining. CD16 was plotted against SSC to compare Circular and Polymorph populations. Positive gating for each fluorochrome parameter was established using FMO controls.
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Fig5: Nuclear morphologic analysis of CD16+ cell populations in adipose tissue confirms flow cytometric phenotypic analysis. Imaging flow cytometry of adipose tissue immune cells was performed as in Figure 3. After exclusion of non-nucleated cells and Hoechst saturating the camera, poorly focused cells, and debris/doublets, CD3-CD14- cells were gated on CD16+ cells. CD16+ cells (~30 cells for each group) were manually selected (Tagged) based on their nuclear morphology to distinguish mononuclear (Circular, panel A) from polymorphonuclear (Polymorph, panel B) cells. The Feature Finder wizard in IDEAS software was used to identify similar cells in the total CD16+ source population (Automated, panels C, E) and to exclude debris and unfocused cells (Automated, panel D). Circularity and Bright Detail Intensity of the Hoechst imagery were the 2 characteristics that best distinguished the manually selected Polymorph and Circular cells. A plot of these 2 parameters for the Tagged and Automated CD16+ populations is depicted. BF = brightfield microscopy, Hoec = Hoechst nuclear staining. CD16 was plotted against SSC to compare Circular and Polymorph populations. Positive gating for each fluorochrome parameter was established using FMO controls.

Mentions: Imaging flow cytometry confirmed other immune cell populations in psoriatic adipose tissue. T cells were verified by positive CD3 staining, round nuclear morphology, and scant cytoplasm (Figure 3, panel D). To determine cell types that express CD16 in adipose tissue, CD3-CD14-CD16+ cells were manually categorized (hand tagged) as having mononuclear (circular, Figure 5, panel A) or polymorphic (polymorph, Figure 5, panel B) nuclei. The Feature Finder wizard in IDEAS software was then used to distinguish cells from the source population with similar morphologic characteristics. This strategy allowed segregation of cellular debris/unfocused cells (Figure 5, panel D), mononuclear cells (Figure 5, panel C), and polymorphonuclear cells (Figure 5, panel E) within the CD16+ population. CD16+ polymorphonuclear cells had multi-lobed (2–3 lobes) nuclei and dense granularity, characteristic of neutrophils. In contrast, CD16+ mononuclear cells had circular nuclei and variable granularity, confirming their identity as NK cells. Further, CD16+ NK cells did not express the macrophage markers HLADRII or CD206 (Additional file 6: Figure S3), nor did they express IL-1β, ACBA1, TLR2, TLR4, CD274, LOX-1, MSR1, CD36, RAGE, CD163, or SR-B1 (Additional file 7: Figure S4).Figure 5


Characterization of immune cells in psoriatic adipose tissue.

Rose S, Stansky E, Dagur PK, Samsel L, Weiner E, Jahanshad A, Doveikis J, Naik HB, Playford MP, McCoy JP, Mehta NN - J Transl Med (2014)

Nuclear morphologic analysis of CD16+ cell populations in adipose tissue confirms flow cytometric phenotypic analysis. Imaging flow cytometry of adipose tissue immune cells was performed as in Figure 3. After exclusion of non-nucleated cells and Hoechst saturating the camera, poorly focused cells, and debris/doublets, CD3-CD14- cells were gated on CD16+ cells. CD16+ cells (~30 cells for each group) were manually selected (Tagged) based on their nuclear morphology to distinguish mononuclear (Circular, panel A) from polymorphonuclear (Polymorph, panel B) cells. The Feature Finder wizard in IDEAS software was used to identify similar cells in the total CD16+ source population (Automated, panels C, E) and to exclude debris and unfocused cells (Automated, panel D). Circularity and Bright Detail Intensity of the Hoechst imagery were the 2 characteristics that best distinguished the manually selected Polymorph and Circular cells. A plot of these 2 parameters for the Tagged and Automated CD16+ populations is depicted. BF = brightfield microscopy, Hoec = Hoechst nuclear staining. CD16 was plotted against SSC to compare Circular and Polymorph populations. Positive gating for each fluorochrome parameter was established using FMO controls.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4197293&req=5

Fig5: Nuclear morphologic analysis of CD16+ cell populations in adipose tissue confirms flow cytometric phenotypic analysis. Imaging flow cytometry of adipose tissue immune cells was performed as in Figure 3. After exclusion of non-nucleated cells and Hoechst saturating the camera, poorly focused cells, and debris/doublets, CD3-CD14- cells were gated on CD16+ cells. CD16+ cells (~30 cells for each group) were manually selected (Tagged) based on their nuclear morphology to distinguish mononuclear (Circular, panel A) from polymorphonuclear (Polymorph, panel B) cells. The Feature Finder wizard in IDEAS software was used to identify similar cells in the total CD16+ source population (Automated, panels C, E) and to exclude debris and unfocused cells (Automated, panel D). Circularity and Bright Detail Intensity of the Hoechst imagery were the 2 characteristics that best distinguished the manually selected Polymorph and Circular cells. A plot of these 2 parameters for the Tagged and Automated CD16+ populations is depicted. BF = brightfield microscopy, Hoec = Hoechst nuclear staining. CD16 was plotted against SSC to compare Circular and Polymorph populations. Positive gating for each fluorochrome parameter was established using FMO controls.
Mentions: Imaging flow cytometry confirmed other immune cell populations in psoriatic adipose tissue. T cells were verified by positive CD3 staining, round nuclear morphology, and scant cytoplasm (Figure 3, panel D). To determine cell types that express CD16 in adipose tissue, CD3-CD14-CD16+ cells were manually categorized (hand tagged) as having mononuclear (circular, Figure 5, panel A) or polymorphic (polymorph, Figure 5, panel B) nuclei. The Feature Finder wizard in IDEAS software was then used to distinguish cells from the source population with similar morphologic characteristics. This strategy allowed segregation of cellular debris/unfocused cells (Figure 5, panel D), mononuclear cells (Figure 5, panel C), and polymorphonuclear cells (Figure 5, panel E) within the CD16+ population. CD16+ polymorphonuclear cells had multi-lobed (2–3 lobes) nuclei and dense granularity, characteristic of neutrophils. In contrast, CD16+ mononuclear cells had circular nuclei and variable granularity, confirming their identity as NK cells. Further, CD16+ NK cells did not express the macrophage markers HLADRII or CD206 (Additional file 6: Figure S3), nor did they express IL-1β, ACBA1, TLR2, TLR4, CD274, LOX-1, MSR1, CD36, RAGE, CD163, or SR-B1 (Additional file 7: Figure S4).Figure 5

Bottom Line: Rarely have these populations been verified with confirmatory methodologies or functional studies.Further, both CD16+CD56(Lo) and CD16-CD56(Hi) NK cells were found to correlate inversely with body mass index.The relationship between the predominant CD16+CD56(Lo) NK cell population and body mass index persisted after adjusting for age, sex, diabetes, and tobacco use.

View Article: PubMed Central - PubMed

ABSTRACT

Background: Adipose tissue normally contains immune cells that regulate adipocyte function and contribute to metabolic disorders including obesity and diabetes mellitus. Psoriasis is associated with increased risk for metabolic disease, which may in part be due to adipose dysfunction, which has not been investigated in psoriasis. There is currently no standardized method for immunophenotyping human adipose tissue. In prior studies, characteristic phenotypic markers of immune cell populations identified in animal models or in other human tissues have been applied in a similar manner to human adipose tissue. Rarely have these populations been verified with confirmatory methodologies or functional studies. Thus, we performed a comprehensive phenotypic and functional analysis of immune cell populations in psoriatic adipose tissue.

Methods: Conventional and imaging flow cytometry were used to define immune cell populations in biopsy specimens of psoriatic adipose tissue (n = 30) including T cells, B cells, NK cells, NKT cells, neutrophils, and macrophages. Relationships between adipose immune cell types and body mass index were determined using Spearman regression analysis, and multivariate linear regression analysis was performed to adjust for cardiometabolic disease risk factors.

Results: These analyses revealed a wide range of cell surface receptors on adipose tissue macrophages, which may serve a dual purpose in immunity and metabolism. Further, both CD16+CD56(Lo) and CD16-CD56(Hi) NK cells were found to correlate inversely with body mass index. The relationship between the predominant CD16+CD56(Lo) NK cell population and body mass index persisted after adjusting for age, sex, diabetes, and tobacco use.

Conclusions: Together, these studies enhance our understanding of adipose immune cell phenotype and function, and demonstrate that examination of adipose tissue may provide greater insight into cardiometabolic pathophysiology in psoriasis.

No MeSH data available.


Related in: MedlinePlus