Pyuza Jeremia J, van Dorst Marloes M A R, Stam Koen, Wammes Linda, König Marion, Kullaya Vesla I, Kruize Yvonne, Huisman Wesley, Andongolile Nikuntufya, Ngowi Anastazia, Shao Elichilia R, Mremi Alex, Hogendoorn Pancras C W, Msuya Sia E, Jochems Simon P, de Steenhuijsen Piters Wouter A A, Yazdanbakhsh Maria
Leiden University Center for Infectious Diseases (LUCID), Leiden University Medical Center, ZA, Leiden, Netherlands.
Department of Pathology, Kilimanjaro Christian Medical Centre, Moshi, Tanzania.
Brain Behav Immun Health. 2024 Sep 20;41:100863. doi: 10.1016/j.bbih.2024.100863. eCollection 2024 Nov.
Immune system and vaccine responses vary across geographical locations worldwide, not only between high and low-middle income countries (LMICs), but also between rural and urban populations within the same country. Lifestyle factors such as housing conditions, exposure to microorganisms and parasites and diet are associated with rural-and urban-living. However, the relationships between these lifestyle factors and immune profiles have not been mapped in detail. Here, we profiled the immune system of 100 healthy Tanzanians living across four rural/urban areas using mass cytometry. We developed a lifestyle score based on an individual's household assets, housing condition and recent dietary history and studied the association with cellular immune profiles. Seventeen out of 80 immune cell clusters were associated with living location or lifestyle score, with eight identifiable only using lifestyle score. Individuals with low lifestyle score, most of whom live in rural settings, showed higher frequencies of NK cells, plasmablasts, atypical memory B cells, T helper 2 cells, regulatory T cells and activated CD4 T effector memory cells expressing CD38, HLA-DR and CTLA-4. In contrast, those with high lifestyle score, most of whom live in urban areas, showed a less activated state of the immune system illustrated by higher frequencies of naïve CD8 T cells. Using an elastic net machine learning model, we identified cellular immune signatures most associated with lifestyle score. Assuming a link between these immune profiles and vaccine responses, these signatures may inform us on the cellular mechanisms underlying poor responses to vaccines, but also reduced autoimmunity and allergies in low- and middle-income countries.
全球各地的免疫系统和疫苗反应各不相同,不仅在高收入国家和中低收入国家(LMICs)之间存在差异,在同一个国家的农村和城市人口之间也存在差异。住房条件、接触微生物和寄生虫以及饮食等生活方式因素与农村和城市生活相关。然而,这些生活方式因素与免疫特征之间的关系尚未得到详细梳理。在这里,我们使用质谱流式细胞术对生活在四个农村/城市地区的100名健康坦桑尼亚人的免疫系统进行了分析。我们根据个人的家庭资产、住房条件和近期饮食史制定了生活方式评分,并研究了其与细胞免疫特征的关联。80个免疫细胞簇中有17个与居住地点或生活方式评分相关,其中8个仅使用生活方式评分即可识别。生活方式评分低的个体(其中大多数生活在农村地区)表现出较高频率的自然杀伤细胞、浆母细胞、非典型记忆B细胞、辅助性T细胞2、调节性T细胞以及表达CD38、HLA-DR和CTLA-4的活化CD4 T效应记忆细胞。相比之下,生活方式评分高的个体(其中大多数生活在城市地区)表现出免疫系统的活化状态较低,这表现为幼稚CD8 T细胞频率较高。使用弹性网络机器学习模型,我们确定了与生活方式评分最相关的细胞免疫特征。假设这些免疫特征与疫苗反应之间存在联系,这些特征可能会让我们了解疫苗反应不佳背后的细胞机制,也能让我们了解低收入和中等收入国家自身免疫和过敏减少的情况。