Analysis of Foxp3, CD25, and CD127 expressed on regulatory T cells in Thai subjects.

Foxp3+ natural regulatory T cells (nTreg) play a distinct role in maintaining self tolerance at the pe-riphery. CD25hi and CD127lo were proposed for the identification and purification of nTreg but they have not been confirmed in non-Caucasian populations. This study examined the sensitivity and purity of Foxp3 nTreg identified by CD25 and CD127 in the peripheral blood of Thai subjects (13 males, 15 females with age range of 20-42 years old). The proportions of nTreg/CD4+ as identified by the different markers were as follows: Foxp3+, 18.3 ± 6.4%; CD25hi, 6.4 ± 3.2%; and CD127lo, 54.3 ± 14.2%. Sensitivity tests showed the following results: CD25hi, 23.1%; CD127lo, 40.6%; CD25hiCD127lo, 7.4%. Purity tests concluded as follows: CD25hi, 63.6%; CD25int, 24.9%; CD25lo, 8.7%, CD127lo, 26.5%; CD127hi, 14.9%, and CD25hiCD127lo, 52.0%. In conclusion, the proportions of nTreg in Thai subjects are similar to Caucasian populations. CD25hi is superior to CD127lo for separating Foxp3+ nTreg. Com-bining CD25hi and CD127lo does not improve the nTreg purity Abbreviations: CD25hi, CD25 highly expressed cells; CD25int, CD25 intermediately expressed cells; CD25lo, CD25 low expressed cells; CD127hi, CD127 high expressed cells; CD127lo, CD127 low expressed cells.

The development and validation of a diabetes risk score for high-risk Thai adults.

OBJECTIVE: To develop a simple risk score to identify high-risk individuals for diabetes screening in Thailand. MATERIAL AND METHOD: The authors analyzed data from 75-g oral glucose tolerance tests performed in 159 males and 270 females, aged 48.4 +/- 10.9 years. RESULTS: The independent variables associated with diabetes included age (p < 0.001), BMI (p < 0.01) and known history of hypertension (HHT) (p < 0.01). The risk equation was Y = 3 age + 5 BMI + 50 HHT. At the cut-off Y value of 240, the sensitivity and specificity for having diabetes were 96.8% and 24.0%, respectively. The positive predictive value was 17.8% and the negative predictive value was 97.8%. Using the equation in a validation group comprising 1617 subjects, it was found that 560 (34.6%) diabetes screenings could be saved while 28 subjects (12.8%) with diabetes would be missed. CONCLUSION: The authors have developed a simple risk scoring method that should be helpful in decreasing the number of unnecessary screening and optimizing the costs associated with diabetes screening.