Why the study?
Specific biological markers for subclinical depression are unknown, with identification relying exclusively on subjective clinical scores and structured interviews.
Does functional bidirectional brain-heart interplay differ between young female adults with subclinical depression and healthy controls?
Does functional bidirectional brain-heart interplay differ between young female adults with subclinical depression and healthy controls?
Subclinical depression is associated with augmented functional central-autonomic control to the heart, suggesting that brain-heart interplay metrics could serve as novel objective biomarkers for mood disorders.
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Brain-heart metrics may aid subclinical depression detection; leaves open prospective validation before biomarker adoption.
Subclinical depression (dysphoria) is a common condition that may increase the risk of major depression and leads to impaired quality of life and severe comorbid somatic diseases. Despite its prevalence, specific biological markers are unknown; consequently, the identification of dysphoria currently relies exclusively on subjective clinical scores and structured interviews. Based on recent neurocardiology studies that link brain and cardiovascular disorders, it was hypothesized that multi-system biomarkers of brain-body interplay may effectively characterize dysphoria. Thus, an ad hoc computational technique was developed to quantify the functional bidirectional brain-heart interplay. Accordingly, 32-channel electroencephalographic and heart rate variability series were obtained from 24 young dysphoric adults and 36 healthy controls. All participants were females of a similar age, and results were obtained during a 5-min resting state. The experimental results suggest that a specific feature of dysphoria is linked to an augmented functional central-autonomic control to the heart, which originates from central, frontopolar, and occipital oscillations and acts through cardiovascular sympathovagal activity. These results enable further development of a large set of novel biomarkers for mood disorders based on comprehensive brain-body measurements.
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Catrambone et al. (2021) studied this question.
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