Natural language indicators of differential gene regulation in the human immune system

Author:

Mehl Matthias R.,Raison Charles L.,Pace Thaddeus W. W.,Arevalo Jesusa M. G.,Cole Steve W.

Abstract

Adverse social conditions have been linked to a conserved transcriptional response to adversity (CTRA) in circulating leukocytes that may contribute to social gradients in disease. However, the CNS mechanisms involved remain obscure, in part because CTRA gene-expression profiles often track external social–environmental variables more closely than they do self-reported internal affective states such as stress, depression, or anxiety. This study examined the possibility that variations in patterns of natural language use might provide more sensitive indicators of the automatic threat-detection and -response systems that proximally regulate autonomic induction of the CTRA. In 22,627 audio samples of natural speech sampled from the daily interactions of 143 healthy adults, both total language output and patterns of function-word use covaried with CTRA gene expression. These language features predicted CTRA gene expression substantially better than did conventional self-report measures of stress, depression, and anxiety and did so independently of demographic and behavioral factors (age, sex, race, smoking, body mass index) and leukocyte subset distributions. This predictive relationship held when language and gene expression were sampled more than a week apart, suggesting that associations reflect stable individual differences or chronic life circumstances. Given the observed relationship between personal expression and gene expression, patterns of natural language use may provide a useful behavioral indicator of nonconsciously evaluated well-being (implicit safety vs. threat) that is distinct from conscious affective experience and more closely tracks the neurobiological processes involved in peripheral gene regulation.

Funder

HHS | National Institutes of Health

Publisher

Proceedings of the National Academy of Sciences

Subject

Multidisciplinary

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