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DOI 10.1002/jcla.23456

Медицинская библиотека · Journal of clinical laboratory analysis · 2020

Evaluation of autoantibodies and immunoglobulin G subclasses in women with suspected macroprolactinemia.

Yu Chao, Fan Fei, Hu Siqi, Meng Lingxin, Xu Dong, Wang Juan, Chen Lu, Liu Jingrui, Dong Ying, Lu Yifan, Shen Min, Zhai Yanhong, Cao Zheng

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Аннотация

BACKGROUND

Macroprolactin mostly composed of an immunoglobulin G (IgG) and a monomeric prolactin (PRL) represents the major circulating PRL form in the patients with macroprolactinemia that are usually asymptomatic and may not require treatment. In this study, we aimed to evaluate the prevalence of antithyroid and antinuclear antibodies, as well as the IgG subclass distributions in the patients suspected for macroprolactinemia.

METHODS

From January to July in 2018, totally 317 patients with elevated PRL were subjected to the polyethylene glycol (PEG) precipitation assay. The patients with recovery rates of ≤60% were subjected for IgG subclass determination and autoantibody testing including thyroid peroxidase antibody (aTPO), antithyroglobulin antibody (aTG), and antinuclear antibodies (ANA).

RESULTS

The higher the post-PEG PRL recovery rates, the less typical hyperprolactinemia symptoms and the higher prevalence of autoantibodies were observed. The IgG1 and IgG3 were the predominant subclasses in the PRL-IgG complexes according to the immunoprecipitation experiments.

CONCLUSION

The patients with post-PEG PRL recovery rates of <40% and 40%-60% were likely to represent two distinct populations of different clinical presentations. The prevalence of autoantibodies and IgG subclasses distribution suggested their pathogenic significance in the development of macroprolactinemia.

Для цитирования: Yu Chao, Fan Fei, Hu Siqi, Meng Lingxin, Xu Dong, Wang Juan, Chen Lu, Liu Jingrui, Dong Ying, Lu Yifan, Shen Min, Zhai Yanhong, Cao Zheng. Evaluation of autoantibodies and immunoglobulin G subclasses in women with suspected macroprolactinemia.. Journal of clinical laboratory analysis. 2020. DOI: 10.1002/jcla.23456.

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