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. 2024 May 11;14(1):202.
doi: 10.1038/s41398-024-02916-w.

Elevated SCN11A concentrations associated with lower serum lipid levels in patients with major depressive disorder

Affiliations

Elevated SCN11A concentrations associated with lower serum lipid levels in patients with major depressive disorder

Ke Xu et al. Transl Psychiatry. .

Abstract

The pathogenesis of major depressive disorder (MDD) involves lipid metabolism. Our earlier research also revealed that MDD patients had much lower total cholesterol (TC) concentrations than healthy controls (HCs). However, it is still unclear why TC decreased in MDD. Here, based on the Ingenuity Knowledge Base's ingenuity pathway analysis, we found that sodium voltage-gated channel alpha subunit 11A (SCN11A) might serve as a link between low lipid levels and MDD. We analyzed the TC levels and used ELISA kits to measure the levels of SCN11A in the serum from 139 MDD patients, and 65 HCs to confirm this theory and explore the potential involvement of SCN11A in MDD. The findings revealed that TC levels were considerably lower and SCN11A levels were remarkably increased in MDD patients than those in HCs, while they were significantly reversed in drug-treatment MDD patients than in drug-naïve MDD patients. There was no significant difference in SCN11A levels among MDD patients who used single or multiple antidepressants, and selective serotonin reuptake inhibitors or other antidepressants. Pearson correlation analysis showed that the levels of TC and SCN11A were linked with the Hamilton Depression Rating Scales score. A substantial association was also found between TC and SCN11A. Moreover, a discriminative model made up of SCN11A was discovered, which produced an area under a curve of 0.9571 in the training set and 0.9357 in the testing set. Taken together, our findings indicated that SCN11A may serve as a link between low lipid levels and MDD, and showed promise as a candidate biomarker for MDD.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1. Potential networks between cholesterol, SCN11A, and major depressive disorder.
According to the Ingenuity Pathway Analysis database, SCN11A may serve as the link between cholesterol and major depressive disorder. ANXA6, annexin A6; EWSR1, ewing sarcoma breakpoint region 1; Lexis1, lipid responsive LXR-induced inhibitor of cholesterol synthesis 1; MANF, mesencephalic astrocyte-derived neurotrophic factor; SCN11A, sodium voltage-gated channel alpha subunit 11A; SLURP2, secreted mammalian Ly6/urokinase plasminogen activator receptor-related protein (SLURP)-2.
Fig. 2
Fig. 2. Serum levels of total cholesterol (TC) and SCN11A in major depressive disorder (MDD) patients.
A Comparison of the serum TC levels between the groups with healthy controls (HCs) and MDD; B Comparison of serum TC levels between the DN-MDD and DT-MDD groups; C Comparison of serum SCN11A levels between the HCs and MDD groups; D Comparison of serum TC levels between the DN-MDD and DT-MDD groups. Data are presented as mean ± S.E.M.
Fig. 3
Fig. 3. Effects of different treatment modalities on TC and SCN11A levels.
A Effects of single antidepressant vs. combined antidepressants on TC levels; B effects of single antidepressant vs. combined antidepressants on SCN11A levels; C, D among the patients receiving single antidepressant, the levels of TC (C) and SCN11A (D) were similar between patients receiving selective serotonin reuptake inhibitor (SSRI) and patients receiving other antidepressants. Data are presented as mean ± S.E.M.
Fig. 4
Fig. 4. Pearson correlation between levels of TC and SCN11A and Hamilton Depression Rating Scale (HDRS) score.
A, B both HDRS score (A) and SCN11A level (B) were significantly negatively correlated with TC level. C SCN11A level was significantly positively correlated with HDRS score.
Fig. 5
Fig. 5. Diagnostic performance of the obtained discriminative model.
A, B A discriminative model consisting of SCN11A discriminated MDD subjects from healthy controls with an area under the receiver operating characteristic curve (AUC) of 0.9571 in the training set (A) and 0.9357 in the testing set (B).

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