Integrated multiomics analysis of salivary exosomes to identify biomarkers associated with changes in mood states and fatigue

Fatigue and other deleterious mood alterations resulting from prolonged efforts such as a long work shift can lead to a decrease in vigilance and cognitive performance, increasing the likelihood of errors during the execution of attention-demanding activities such as piloting an aircraft or performing medical procedures. Thus, a method to rapidly and objectively assess the risk for such cognitive fatigue would be of value. The objective of the study was the identification in saliva-borne exosomes of molecular signals associated with changes in mood and fatigue that may increase the risk of reduced cognitive performance. Using integrated multiomics analysis of exosomes from the saliva of medical residents before and after a 12 h work shift, researchers from the UCLA David Geffen School of Medicine observed changes in the abundances of several proteins and miRNAs that were associated with various mood states, and specifically fatigue, as determined by a Profile of Mood States questionnaire. The findings herein point to a promising protein biomarker, phosphoglycerate kinase 1 (PGK1), that was associated with fatigue and displayed changes in abundance in saliva, and the researchers suggest a possible biological mechanism whereby the expression of the PGK1 gene is regulated by miR3185 in response to fatigue. Overall, these data suggest that multiomics analysis of salivary exosomes has merit for identifying novel biomarkers associated with changes in mood states and fatigue. The promising biomarker protein presents an opportunity for the development of a rapid saliva-based test for the assessment of these changes.

Study flow scheme for Profile of Mood States (PoMS) assessment, sample collection, processing, and analysis

(A) Resident participants (n = 36) were enrolled. (B) Participants completed the PoMS questionnaire and (C) collected saliva before a (D) 12 h work shift. (E) Saliva was collected, and the (F) PoMS questionnaire completed again after the work shift. (G) Total Mood Disturbance (TMD) and subscale (for example, fatigue–inertia, FI) scores were calculated. Isolation of exosomes comprised (H) centrifugation, (I) binding of exosomes to exosome marker-specific (and in one instance, neuronal-marker specific) antibody-conjugated Dynabeads, (J) release of exosomes for processing, and omics analyses. Based on TMD, participant samples were separated into Test (decrease in TMD or ‘improved’ mood), Discovery (increased in TMD or mood disturbance), and Validation (little/no change in TMD) groups. Exosomes from each group underwent the analyses shown.

Cohn W, Zhu C, Campagna J et al. (2022) Integrated Multiomics Analysis of Salivary Exosomes to Identify Biomarkers Associated with Changes in Mood States and Fatigue. Int J Mol Sci 23(9), 5257. [article]

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