02528nas a2200253 4500000000100000008004100001260001200042653001000054653001400064653001200078653002200090653002100112100001200133700001300145700001300158700001700171700001300188700001200201700001200213700001400225245015200239520186900391022001402260 2025 d c10/202510aPGL-110aCytokines10aleprosy10aLeprosy reactions10aquantitative PCR1 aJoshi R1 aSaikia U1 aNarang T1 aMadakshira M1 aSaikia B1 aDogra S1 aSingh I1 aRadotra B00aAssessment of RLEP Copy Number in Leprosy Patient Skin Biopsies: Correlations With Cytokine and Anti-PGL-1 Antibody Levels Pre- and Post-Treatment.3 a

Background

New cases of leprosy continue to occur even after significant efforts have been made to eliminate them. Histopathology is the gold standard for diagnosis, although it is not useful for disease monitoring. This study aimed to assess repetitive element (RLEP) gene copy number in pre- and post-treatment skin biopsies of patients with leprosy using quantitative polymerase chain reaction (qPCR) and its correlation with cytokine and anti-PGL-1 antibody levels for leprosy diagnosis and as a marker for risk prediction of leprosy reactions.

Materials and Methods

A total of 92 patients with a clinical diagnosis of leprosy were prospectively included, with follow-up in 40 patients. The anti-PGL-1 antibody levels and cytokine levels of interferon-γ (IFN-γ) and interleukin-4 (IL-4) in serum samples were determined by ELISA. QPCR was performed after DNA extraction from formalin-fixed paraffin-embedded skin biopsies.

Results

RLEP copy number was significantly higher in the lepromatous spectrum than in the tuberculoid spectrum (P < 0.001). Phenolic glycolipid (P = 0.019) and IFN-γ (P < 0.001) levels were significantly higher in patients with leprosy than in healthy controls. In comparison, the pre- and post-treatment groups showed a significant decrease in RLEP copy number (P = 0.002), anti-PGL-1 antibody levels (P = 0.009), IFN-γ (P 0.001), and IL-4 (P < 0.001) levels in the latter.

Conclusions

qPCR is a sensitive diagnostic test, and in conjunction with anti-PGL-1 antibody and cytokine levels, clinical and histomorphologic features can be used for the appropriate classification of leprosy, diagnosis of atypical cases, disease monitoring, and risk prediction of leprosy reactions.

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