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Simultaneous analysis of T helper subsets (Th1, Th2, Th9, Th17, Th22, Tfh, Tr1 and Tregs) markers expression in periapical lesions reveals multiple cytokine clusters accountable for lesions activity and inactivity status.

Araujo-Pires AC, Francisconi CF, Biguetti CC, Cavalla F, Aranha AM, Letra A, Trombone AP, Faveri M, Silva RM, Garlet GP - J Appl Oral Sci (2014 Jul-Aug)

Bottom Line: Five clusters were identified in inactive lesion groups, being the variance in the expression levels of IL-17, IL-10, FOXp3, IFN-γ, IL-9, IL-33 and IL-4 statistically significant (KW p<0.05).There is a clear dichotomy in the profile of cytokine expression in inactive and active periapical lesions.While the widespread cytokine expression seems to be a feature of chronic lesions, hierarchical cluster analysis demonstrates the association of TNF-α, IL-21, IL-17 and IFN-γ with lesions activity, and the association of FOXP3, IL-10, IL-9, IL-4 and IL-22 with lesions inactivity.

View Article: PubMed Central - PubMed

Affiliation: Department of Biological Sciences, Bauru School of Dentistry, University of São Paulo, Bauru, SP, Brazil.

ABSTRACT

Unlabelled: Previous studies demonstrate that the balance between pro- and anti-inflammatory mediators determines the stable or progressive nature of periapical granulomas by modulating the balance of the osteoclastogenic factor RANKL and its antagonist OPG. However, the cytokine networks operating in the development of periapical lesions are quite more complex than what the simple pro- versus anti-inflammatory mediators' paradigm suggests. Here we simultaneously investigated the patterns of Th1, Th2, Th9, Th17, Th22, Thf, Tr1 and Tregs cytokines/markers expression in human periapical granulomas.

Methods: The expression of TNF-α, IFN-γ, IL-17A, IL23, IL21, IL-33, IL-10, IL-4, IL-9, IL-22, FOXp3 markers (via RealTimePCR array) was accessed in active/progressive (N=40) versus inactive/stable (N=70) periapical granulomas (as determined by RANKL/OPG expression ratio), and also to compare these samples with a panel of control specimens (N=26). A cluster analysis of 13 cytokine levels was performed to examine possible clustering between the cytokines in a total of 110 granulomas.

Results: The expression of all target cytokines was higher in the granulomas than in control samples. TNF-α, IFN-γ, IL-17A and IL-21 mRNA levels were significantly higher in active granulomas, while in inactive lesions the expression levels of IL-4, IL-9, IL-10, IL-22 and FOXp3 were higher than in active granulomas. Five clusters were identified in inactive lesion groups, being the variance in the expression levels of IL-17, IL-10, FOXp3, IFN-γ, IL-9, IL-33 and IL-4 statistically significant (KW p<0.05). Three clusters were identified in active lesions, being the variance in the expression levels of IL-22, IL-10, IFN-γ, IL-17, IL-33, FOXp3, IL-21 and RANKL statistically significant (KW p<0.05).

Conclusion: There is a clear dichotomy in the profile of cytokine expression in inactive and active periapical lesions. While the widespread cytokine expression seems to be a feature of chronic lesions, hierarchical cluster analysis demonstrates the association of TNF-α, IL-21, IL-17 and IFN-γ with lesions activity, and the association of FOXP3, IL-10, IL-9, IL-4 and IL-22 with lesions inactivity.

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Patterns of cytokine expression in active and inactive periapical granulomas.Total RNA was extracted from periapical granulomas (N=110) and periodontalligament control samples (N=26), and levels of TNF-α(classic pro-inflammmatorycytokine), IL-10 (Treg and Tr1 marker), IFN-γ (Th1 marker), IL-4 (Th2 marker),FOXp3 (Treg marker), CTLA4 (Treg marker), TGF-β (Treg and Th3 marker), IL-9(Th9 marker), IL-17A (Th17 marker), IL-17F (Th17 marker), IL-21 (Th17 or Tfhmarker), IL-23 (Th17 marker) and IL-22 (Th22 marker) were measuredquantitatively by RealTimePCR using TaqMan chemistry. Based on the profile ofRANKL/OPG expression29, the lesions were then categorized into active(RANKL>OPG) or inactive (RANKL≈OPG and RANKL<OPG)
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f02: Patterns of cytokine expression in active and inactive periapical granulomas.Total RNA was extracted from periapical granulomas (N=110) and periodontalligament control samples (N=26), and levels of TNF-α(classic pro-inflammmatorycytokine), IL-10 (Treg and Tr1 marker), IFN-γ (Th1 marker), IL-4 (Th2 marker),FOXp3 (Treg marker), CTLA4 (Treg marker), TGF-β (Treg and Th3 marker), IL-9(Th9 marker), IL-17A (Th17 marker), IL-17F (Th17 marker), IL-21 (Th17 or Tfhmarker), IL-23 (Th17 marker) and IL-22 (Th22 marker) were measuredquantitatively by RealTimePCR using TaqMan chemistry. Based on the profile ofRANKL/OPG expression29, the lesions were then categorized into active(RANKL>OPG) or inactive (RANKL≈OPG and RANKL<OPG)

Mentions: In the view of the distinctly divergent cytokine profile between controls andlesions, cluster analysis was only performed with the lesion data in order to avoidbiased associations. Initial cluster analysis performed with all (active + inactive)the lesions (Figure 2) resulted in theidentification of 2 major clusters, comprised by 41 and 69 samples, presenting a 98%match with the clustering based in the RANKL/OPG patterns29. Considering such clear dichotomy, we performedadditional cluster analysis within active and inactive lesions groups. In inactivelesions group (Table 1), 5 clusters wereidentified, being the variance in the expression levels of IL-17, IL-10, FOXp3,IFN-γ, IL-9, IL-33 and IL-4 statistically significant (KW p<0.05) among theclusters of inactive lesions, while IL-22, OPG, IL-23, TNF-α, RANKL and IL-21 levelspresented KW p values higher than 0.05. When active lesions were analyzed (Table 2), 3 clusters were identified, being thevariance in the expression levels of IL-22, IL-10, IFN-γ, IL-17, IL-33, FOXp3, IL-21and RANKL statistically significant (KW p<0.05) among the active lesions clusters,while IL-9, IL-4, TNF-α, OPG and IL-23 levels presented KW p values higher than0.05.


Simultaneous analysis of T helper subsets (Th1, Th2, Th9, Th17, Th22, Tfh, Tr1 and Tregs) markers expression in periapical lesions reveals multiple cytokine clusters accountable for lesions activity and inactivity status.

Araujo-Pires AC, Francisconi CF, Biguetti CC, Cavalla F, Aranha AM, Letra A, Trombone AP, Faveri M, Silva RM, Garlet GP - J Appl Oral Sci (2014 Jul-Aug)

Patterns of cytokine expression in active and inactive periapical granulomas.Total RNA was extracted from periapical granulomas (N=110) and periodontalligament control samples (N=26), and levels of TNF-α(classic pro-inflammmatorycytokine), IL-10 (Treg and Tr1 marker), IFN-γ (Th1 marker), IL-4 (Th2 marker),FOXp3 (Treg marker), CTLA4 (Treg marker), TGF-β (Treg and Th3 marker), IL-9(Th9 marker), IL-17A (Th17 marker), IL-17F (Th17 marker), IL-21 (Th17 or Tfhmarker), IL-23 (Th17 marker) and IL-22 (Th22 marker) were measuredquantitatively by RealTimePCR using TaqMan chemistry. Based on the profile ofRANKL/OPG expression29, the lesions were then categorized into active(RANKL>OPG) or inactive (RANKL≈OPG and RANKL<OPG)
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4126831&req=5

f02: Patterns of cytokine expression in active and inactive periapical granulomas.Total RNA was extracted from periapical granulomas (N=110) and periodontalligament control samples (N=26), and levels of TNF-α(classic pro-inflammmatorycytokine), IL-10 (Treg and Tr1 marker), IFN-γ (Th1 marker), IL-4 (Th2 marker),FOXp3 (Treg marker), CTLA4 (Treg marker), TGF-β (Treg and Th3 marker), IL-9(Th9 marker), IL-17A (Th17 marker), IL-17F (Th17 marker), IL-21 (Th17 or Tfhmarker), IL-23 (Th17 marker) and IL-22 (Th22 marker) were measuredquantitatively by RealTimePCR using TaqMan chemistry. Based on the profile ofRANKL/OPG expression29, the lesions were then categorized into active(RANKL>OPG) or inactive (RANKL≈OPG and RANKL<OPG)
Mentions: In the view of the distinctly divergent cytokine profile between controls andlesions, cluster analysis was only performed with the lesion data in order to avoidbiased associations. Initial cluster analysis performed with all (active + inactive)the lesions (Figure 2) resulted in theidentification of 2 major clusters, comprised by 41 and 69 samples, presenting a 98%match with the clustering based in the RANKL/OPG patterns29. Considering such clear dichotomy, we performedadditional cluster analysis within active and inactive lesions groups. In inactivelesions group (Table 1), 5 clusters wereidentified, being the variance in the expression levels of IL-17, IL-10, FOXp3,IFN-γ, IL-9, IL-33 and IL-4 statistically significant (KW p<0.05) among theclusters of inactive lesions, while IL-22, OPG, IL-23, TNF-α, RANKL and IL-21 levelspresented KW p values higher than 0.05. When active lesions were analyzed (Table 2), 3 clusters were identified, being thevariance in the expression levels of IL-22, IL-10, IFN-γ, IL-17, IL-33, FOXp3, IL-21and RANKL statistically significant (KW p<0.05) among the active lesions clusters,while IL-9, IL-4, TNF-α, OPG and IL-23 levels presented KW p values higher than0.05.

Bottom Line: Five clusters were identified in inactive lesion groups, being the variance in the expression levels of IL-17, IL-10, FOXp3, IFN-γ, IL-9, IL-33 and IL-4 statistically significant (KW p<0.05).There is a clear dichotomy in the profile of cytokine expression in inactive and active periapical lesions.While the widespread cytokine expression seems to be a feature of chronic lesions, hierarchical cluster analysis demonstrates the association of TNF-α, IL-21, IL-17 and IFN-γ with lesions activity, and the association of FOXP3, IL-10, IL-9, IL-4 and IL-22 with lesions inactivity.

View Article: PubMed Central - PubMed

Affiliation: Department of Biological Sciences, Bauru School of Dentistry, University of São Paulo, Bauru, SP, Brazil.

ABSTRACT

Unlabelled: Previous studies demonstrate that the balance between pro- and anti-inflammatory mediators determines the stable or progressive nature of periapical granulomas by modulating the balance of the osteoclastogenic factor RANKL and its antagonist OPG. However, the cytokine networks operating in the development of periapical lesions are quite more complex than what the simple pro- versus anti-inflammatory mediators' paradigm suggests. Here we simultaneously investigated the patterns of Th1, Th2, Th9, Th17, Th22, Thf, Tr1 and Tregs cytokines/markers expression in human periapical granulomas.

Methods: The expression of TNF-α, IFN-γ, IL-17A, IL23, IL21, IL-33, IL-10, IL-4, IL-9, IL-22, FOXp3 markers (via RealTimePCR array) was accessed in active/progressive (N=40) versus inactive/stable (N=70) periapical granulomas (as determined by RANKL/OPG expression ratio), and also to compare these samples with a panel of control specimens (N=26). A cluster analysis of 13 cytokine levels was performed to examine possible clustering between the cytokines in a total of 110 granulomas.

Results: The expression of all target cytokines was higher in the granulomas than in control samples. TNF-α, IFN-γ, IL-17A and IL-21 mRNA levels were significantly higher in active granulomas, while in inactive lesions the expression levels of IL-4, IL-9, IL-10, IL-22 and FOXp3 were higher than in active granulomas. Five clusters were identified in inactive lesion groups, being the variance in the expression levels of IL-17, IL-10, FOXp3, IFN-γ, IL-9, IL-33 and IL-4 statistically significant (KW p<0.05). Three clusters were identified in active lesions, being the variance in the expression levels of IL-22, IL-10, IFN-γ, IL-17, IL-33, FOXp3, IL-21 and RANKL statistically significant (KW p<0.05).

Conclusion: There is a clear dichotomy in the profile of cytokine expression in inactive and active periapical lesions. While the widespread cytokine expression seems to be a feature of chronic lesions, hierarchical cluster analysis demonstrates the association of TNF-α, IL-21, IL-17 and IFN-γ with lesions activity, and the association of FOXP3, IL-10, IL-9, IL-4 and IL-22 with lesions inactivity.

Show MeSH
Related in: MedlinePlus