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. 2023 Aug 5;15(8):e42985.
doi: 10.7759/cureus.42985. eCollection 2023 Aug.

Non-targeted Metabolomics Analysis Reveals Distinct Metabolic Profiles Between Positive and Negative Emotional Tears of Humans: A Preliminary Study

Affiliations

Non-targeted Metabolomics Analysis Reveals Distinct Metabolic Profiles Between Positive and Negative Emotional Tears of Humans: A Preliminary Study

Hao Liang et al. Cureus. .

Abstract

Background Basal, reflex, and emotional tears differ in chemical components. It is not yet known whether chemical differences exist in tears of different emotions. We investigated the biochemical basis of emotional tears by performing non-targeted metabolomics analyses of positive and negative emotional tears of humans. Methods Samples of reflex, negative, and positive emotional tears were obtained from 12 healthy college participants (11 females and one male). Untargeted metabolomics was performed to identify metabolites in different types of tears. The differentially altered metabolites were screened and assessed using univariate and multivariate analyses. Results The orthogonal partial least squares discriminant analysis model showed that reflex, negative, and positive emotional tears were clearly separated. A total of 133 significantly differentially expressed metabolites of electrospray ionization source (ESI-) mode were identified between negative and positive emotional tears. The top 50 differentially expressed metabolites between negative and positive emotional tears were highly correlated. Pathway analysis revealed that secretion of negative emotional tears was associated with some synapses in the brain, regulation of a series of endocrine hormones, including the estrogen signaling pathway, and inflammation activities, while secretion of positive emotional tears was correlated with biotin and caffeine metabolism. Conclusions It is indicated that metabolic profiles of reflex, positive, and negative emotional tears of humans are distinct, and secretion of the tears involves distinct biological activities. Therefore, we present a chemical method for detecting human emotions, which may become a powerful tool for the diagnosis of mental diseases and the identification of fake tears.

Keywords: emotional evaluation; emotional tears; metabolic profile; metabolomics; tears; types of tears.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Workflow of tears collection and analysis.
OPLS-DA: orthogonal partial least squares discriminant analysis.
Figure 2
Figure 2. OPLS-DA score plots of multivariate statistical analysis between reflex tears, negative emotional tears, and positive emotional tears.
C Group: reflex tears; S Group: negative emotional tears; M Group: positive emotional tears; OPLS-DA: orthogonal partial least squares discriminant analysis; ESI: electrospray ionization.
Figure 3
Figure 3. Venn plots of screened metabolites between reflex tears, negative emotional tears, and positive emotional tears.
ESI: electrospray ionization.
Figure 4
Figure 4. Correlation plots of the top 50 differentially expressed metabolites between reflex tears, negative emotional tears, and positive emotional tears.
C Group: reflex tears; S Group: negative emotional tears; M Group: positive emotional tears; ESI: electrospray ionization.
Figure 5
Figure 5. KEGG enrichment scatter plots of the identified differentially expressed metabolites between reflex tears, negative emotional tears, and positive emotional tears.
C Group: reflex tears; S Group: negative emotional tears; M Group: positive emotional tears; KEGG: Kyoto Encyclopedia of Genes and Genomes; ESI: electrospray ionization; GnRH: gonadotropin-releasing hormone.
Figure 6
Figure 6. Total ion chromatogram (TIC) of tears in the quality control (QC) samples.
Figure 7
Figure 7. Principal component analysis (PCA) of whole samples.
C Group: reflex tears; S Group: negative emotional tears; M Group: positive emotional tears; ESI: electrospray ionization.
Figure 8
Figure 8. Validation analysis by comparing the goodness-of-fit (R2 and Q2) of OPLS-DA models with the goodness-of-fit of 200 Y-permutated models.
C Group: reflex tears; S Group: negative emotional tears; M Group: positive emotional tears; OPLS-DA: orthogonal partial least squares discriminant analysis; ESI: electrospray ionization.
Figure 9
Figure 9. Volcano plots of differentially expressed metabolites.
C Group: reflex tears; S Group: negative emotional tears; M Group: positive emotional tears; ESI: electrospray ionization.
Figure 10
Figure 10. Heatmaps of cluster analysis of the overall differentially expressed metabolites.
A: ESI+ C vs. S; B: ESI+ C vs. M; C: ESI- C vs. M; D: ESI- S vs. M; C Group: reflex tears; S Group: negative emotional tears; M Group: positive emotional tears; ESI: electrospray ionization.

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