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母乳免疫球蛋白组。

The Breast Milk Immunoglobulinome.

机构信息

Physiology Section, Department of Biochemistry and Physiology, Faculty of Pharmacy and Food Science, University of Barcelona (UB), 08028 Barcelona, Spain.

Nutrition and Food Safety Research Institute (INSA-UB), 08921 Santa Coloma de Gramenet, Spain.

出版信息

Nutrients. 2021 May 26;13(6):1810. doi: 10.3390/nu13061810.

Abstract

Breast milk components contribute to the infant's immune development and protection, and among other immune factors, immunoglobulins (Igs) are the most studied. The presence of IgA in milk has been known for a long time; however, less information is available about the presence of other Igs such as IgM, IgG, and their subtypes (IgG1, IgG2, IgG3, and IgG4) or even IgE or IgD. The total Ig concentration and profile will change during the course of lactation; however, there is a great variability among studies due to several variables that limit establishing a clear pattern. In this context, the aim of this review was firstly to shed light on the Ig concentration in breast milk based on scientific evidence and secondly to study the main factors contributing to such variability. A search strategy provided only 75 studies with the prespecified eligibility criteria. The concentrations and proportions found have been established based on the intrinsic factors of the study-such as the sampling time and quantification technique-as well as participant-dependent factors, such as lifestyle and environment. All these factors contribute to the variability of the immunoglobulinome described in the literature and should be carefully addressed for further well-designed studies and data interpretation.

摘要

母乳成分有助于婴儿的免疫发育和保护,在其他免疫因素中,免疫球蛋白(Ig)是研究最多的。很长一段时间以来,人们都知道母乳中存在 IgA;然而,关于其他 Ig 的存在情况,如 IgM、IgG 及其亚型(IgG1、IgG2、IgG3 和 IgG4),甚至 IgE 或 IgD 的信息较少。在哺乳期,总 Ig 浓度和谱会发生变化;然而,由于限制建立明确模式的几个变量,研究之间存在很大的变异性。在这种情况下,本综述的目的首先是根据科学证据阐明母乳中 Ig 浓度,其次是研究导致这种变异性的主要因素。搜索策略仅提供了 75 项符合预定纳入标准的研究。所发现的浓度和比例是基于研究的内在因素(如采样时间和定量技术)以及参与者相关因素(如生活方式和环境)确定的。所有这些因素都会导致文献中描述的免疫球蛋白组的变异性,在进一步进行精心设计的研究和数据解释时,应仔细考虑这些因素。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd98/8230140/3b1463e2695d/nutrients-13-01810-g001.jpg

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