孤独感是如何“深入骨髓”并在生物学上扎根的?
How does loneliness "get under the skin" to become biologically embedded?
机构信息
Department of Psychology, University of Minnesota Twin Cities, Minneapolis, MN, USA.
出版信息
Biodemography Soc Biol. 2023 Oct-Dec;68(4):115-148. doi: 10.1080/19485565.2023.2260742. Epub 2023 Nov 27.
Loneliness is linked to declining physical health across cardiovascular, inflammatory, metabolic, and cognitive domains. As a result, loneliness is increasingly being recognized as a public health threat, though the mechanisms that have been studied do not yet explain all loneliness-related health risk. Potential mechanisms include loneliness having 1.) direct, causal impacts on health, possibly maintained by epigenetic modification, 2.) indirect effects mediated through health-limiting behaviors, and 3.) artifactual associations perhaps related to genetic overlap and reverse causation. In this scoping review, we examine the evidence surrounding each of these pathways, with a particular emphasis on emerging research on epigenetic effects, in order to evaluate how loneliness becomes biologically embedded. We conclude that there are significant gaps in our knowledge of how psychosocial stress may lead to physiological changes, so more work is needed to understand if, how, and when loneliness has a direct influence on health. Hypothalamic-pituitary adrenocortical axis disruptions that lead to changes in gene expression through methylation and the activity of transcription factor proteins are one promising area of research but are confounded by a number of unmeasured factors. Therefore, wok is needed using causally informative designs, such as twin and family studies and intensively longitudinal diary studies.
孤独感与心血管、炎症、代谢和认知领域的身体健康状况下降有关。因此,孤独感正日益被视为一种公共健康威胁,尽管已研究的机制仍不能解释所有与孤独相关的健康风险。潜在机制包括孤独感对健康有直接的因果影响,这可能是通过表观遗传修饰来维持的;通过限制健康的行为产生间接影响;以及可能与遗传重叠和反向因果关系有关的人为关联。在本范围综述中,我们研究了这些途径的证据,特别强调了关于表观遗传效应的新兴研究,以评估孤独感如何在生物学上得以体现。我们的结论是,我们对社会心理压力如何导致生理变化的认识存在重大差距,因此,需要开展更多的工作来了解孤独感是否、如何以及何时对健康产生直接影响。导致通过甲基化和转录因子蛋白活性改变基因表达的下丘脑-垂体-肾上腺皮质轴紊乱是一个很有前途的研究领域,但受到许多未测量因素的干扰。因此,需要使用因果信息丰富的设计(如双胞胎和家庭研究以及密集纵向日记研究)来开展相关工作。