Th1/Th2 Balance in Young Subjects: Relationship with Cytokine Levels and Metabolic Profile

J Inflamm Res. 2021 Dec 6:14:6587-6600. doi: 10.2147/JIR.S342545. eCollection 2021.

Abstract

Purpose: We aim to identify Th1 and Th2 cell clusters in young subjects, including their clinical and metabolic characteristics and the Th1/Th2 balance.

Patients and methods: A total of 100 participants were included. The frequencies of Th1 and Th2 cells in peripheral blood were determined by flow cytometry. Serum C-reactive protein was measured using a turbidimetric assay, and insulin levels were quantified with an enzyme-linked immunosorbent assay. Circulating cytokine levels were analyzed using a multiplex system.

Results: A cluster analysis was performed to determine the Th1/Th2 balance in a group of young people, and 3 clusters were formed with the following characteristics: 1) subjects with a higher prevalence of hyperglycemia (38%), dyslipidemia (38-75%), and insulin resistance (50%), as well as a higher percentage of Th1 cells and Th1/Th2 ratio, including elevated IFN-ɣ levels; 2) subjects with a lower prevalence of hyperglycemia (23%) and insulin resistance (15.4%), but a higher prevalence of dyslipidemia (8-85%) with a predominance of Th2 cells, and lower Th1/Th2 ratio; 3) subjects with a lower prevalence of hyperglycemia (6%), insulin resistance (41%), and dyslipidemia (10-63%), as well as a balance of Th1 and Th2 cells and lower Th1/Th2 ratio, including low IFN-ɣ levels. Positive correlations between Th1 cells with IFN-γ, IL-12, and IL-1β and between Th2 cells with IFN-γ, IL-2, and IL-4 were found (p < 0.05). A significant increase in Th1 cells was observed in the presence of hyperglycemia and high LDL-C levels, as well as increased Th2 cells in the absence of abdominal obesity and high blood pressure, including low HDL-C levels. The Th1/Th2 ratio was higher in the group with high cardiometabolic risk (p = 0.03).

Conclusion: Th1/Th2 balance is related to metabolic abnormalities that may occur in young population, and thus the timely identification of different phenotypes may help predict an increased cardiometabolic risk.

Keywords: IFN-ɣ levels; Th1 cells; Th2 cells; dyslipidemias; hyperglycemia.