Center for Happiness Studies, Seoul National University, South Korea.
Departments of Medicine and Psychiatry & Biobehavioral Sciences, University of California, Los Angeles, USA.
Psychoneuroendocrinology. 2023 Sep;155:106342. doi: 10.1016/j.psyneuen.2023.106342. Epub 2023 Jul 22.
Social connections are crucial to human health and well-being. Previous research on molecular mechanisms in health has focused primarily on the individual-level perception of social connections (e.g., loneliness). This study adopted socio-centric social network analysis that includes all social ties from the entire population of interest to examine the group-level social connections and their association with a molecular genomic measure of health.
Using socio-centric (global) social network data from an entire village in Korea, we investigated how social network characteristics are related to immune cell gene expression among older adults. Blood samples were collected (N = 53, 65-79 years) and mixed effect linear model analyses were performed to examine the association between social network characteristics and Conserved Transcriptional Response to Adversity (CTRA) RNA expression patterns.
Social network positions measured by k-core score, the degree of cohesive core positions in an entire village, were significantly associated with CTRA downregulation. Such associations emerged above and beyond the effects of perceived social isolation (loneliness) and biobehavioral risk factors (smoking, alcohol, BMI, etc.). Social network size, defined as degree centrality, was also associated with reduced CTRA gene expression, but its association mimicked that of perceived social isolation (loneliness).
The current findings implicate community-level social network characteristics in the regulation of individual human genome function above and beyond individual-level perceptions of connectedness.
社会关系对人类健康和幸福至关重要。以前关于健康的分子机制的研究主要集中在个体层面感知到的社会关系(例如孤独感)上。本研究采用以社区为中心的社会网络分析方法,该方法包括感兴趣的整个人群的所有社会关系,以检验群体层面的社会关系及其与健康的分子基因组测量值的关联。
使用来自韩国一个村庄的以社区为中心(全局)的社会网络数据,我们调查了社会网络特征如何与老年人的免疫细胞基因表达相关。采集了血液样本(N=53,65-79 岁),并进行混合效应线性模型分析,以检验社会网络特征与逆境保守转录反应(CTRA)RNA 表达模式之间的关联。
通过核心分数(k-核心分数)衡量的社会网络位置,即整个村庄中凝聚核心位置的程度,与 CTRA 下调显著相关。这种关联超出了感知到的社会孤立(孤独感)和生物行为风险因素(吸烟、饮酒、BMI 等)的影响。网络规模,定义为中心度,也与 CTRA 基因表达的减少相关,但它的关联类似于感知到的社会孤立(孤独感)。
目前的研究结果表明,社区层面的社会网络特征在调节个体人类基因组功能方面的作用超出了个体层面的联系感。