Special Issue: The intersection of inflammation and metabolism in neuropsychiatric disorders

Altered neural activity in the reward-related circuit associated with anhedonia in mild to moderate Major Depressive Disorder

BACKGROUND

Anhedonia is a significant predictor of disease progression and treatment outcomes in Major Depressive Disorder (MDD), linked to reward network dysfunctions. However, understanding of its underlying neural mechanisms remains limited. This study aimed to investigate the brain functional mechanisms underlying MDD with anhedonia using resting-state functional magnetic resonance imaging (rs-fMRI).

METHODS

The Snaith-Hamilton Pleasure Scale (SHAPS) was used to evaluation MDD with anhedonia (anMDD) and non-anhedonia MDD (non-anMDD). Forty-eight patients with anMDD, Forty-four patients with non-anMDD, and Fifty healthy controls (HCs) were enrolled for the fMRI scans. A seed-based functional connectivity (FC) method was employed to explore reward network abnormalities.

RESULTS

anMDD patients exhibited lower FC values in Ventral Striatum (VS), right lateral Ventral Tegmental Area (VTA_R), left Thalamus (THA_L), and higher FC values in Ventromedial Prefrontal Cortex (vmPFC), left Anterior Insula (AI_L), and Presupplementary Motor Area (Pre-SMA) compared to HCs. Comparing anMDD to non-anMDD, significant differences were observed in FC values of VS, vmPFC, Pre-SMA, and THA_L regions. Correlation analysis revealed positive correlations between FC values of VS_R and NAc_R, as well as THA_L and Cerebellum_Crus1_L, with SHAPS scores. Negative correlations were observed between FC values of Pre-SMA and the right caudate, and between vmPFC and Frontal_Mid_Orb_L, and SHAPS scores.

CONCLUSION

Both anMDD and non-anMDD groups demonstrated abnormal FCs in the reward network. These findings indicate distinct roles of reward-related circuits in the two subtypes, contributing to a refined understanding of depression phenotypes and potential directions for targeted interventions.

Immuno-metabolic profile of patients with psychotic disorders and metabolic syndrome. Results from the FACE-SZ cohort

Background

Metabolic syndrome (MetS) is a highly prevalent and harmful medical disorder often comorbid with psychosis where it can contribute to cardiovascular complications. As immune dysfunction is a key shared component of both MetS and schizophrenia (SZ), this study investigated the relationship between immune alterations and MetS in patients with SZ, whilst controlling the impact of confounding clinical characteristics including psychiatric symptoms and comorbidities, history of childhood maltreatment and psychotropic treatments.

Method

A total of 310 patients meeting DSM-IV criteria for SZ or schizoaffective disorders (SZA), with or without MetS, were systematically assessed and included in the FondaMental Advanced Centers of Expertise for Schizophrenia (FACE-SZ) cohort. Detailed clinical characteristics of patients, including psychotic symptomatology, psychiatric comorbidities and history of childhood maltreatment were recorded and the serum levels of 18 cytokines were measured. A penalized regression method was performed to analyze associations between inflammation and MetS, whilst controlling for confounding factors.

Results

Of the total sample, 25% of patients had MetS. Eight cytokines were above the lower limit of detection (LLOD) in more than 90% of the samples and retained in downstream analysis. Using a conservative Variable Inclusion Probability (VIP) of 75%, we found that elevated levels of interleukin (IL)-6, IL-7, IL-12/23 p40 and IL-16 and lower levels of tumor necrosis factor (TNF)-α were associated with MetS. As for clinical variables, age, sex, body mass index (BMI), diagnosis of SZ (not SZA), age at the first episode of psychosis (FEP), alcohol abuse, current tobacco smoking, and treatment with antidepressants and anxiolytics were all associated with MetS.

Conclusion

We have identified five cytokines associated with MetS in SZ suggesting that patients with psychotic disorders and MetS are characterized by a specific “immuno-metabolic” profile. This may help to design tailored treatments for this subgroup of patients with both psychotic disorders and MetS, taking one more step towards precision medicine in psychiatry.

High S100B Levels Predict Antidepressant Response in Patients With Major Depression Even When Considering Inflammatory and Metabolic Markers

BACKGROUND

The relationship between antidepressant response and glial, inflammatory, and metabolic markers is poorly understood in depression. This study assessed the ability of biological markers to predict antidepressant response in major depressive disorder (MDD).

METHODS

We included 31 MDD outpatients treated with escitalopram or sertraline for 8 consecutive weeks. The Montgomery-Åsberg Depression Rating Scale (MADRS) was administered at baseline and at week 4 and 8 of treatment. Concomitantly, blood samples were collected for the determination of serum S100B, C-reactive protein (CRP), and high-density lipoprotein cholesterol (HDL)-C levels. Treatment response was defined as ≥50% improvement in the MADRS score from baseline to either week 4 or 8. Variables associated with treatment response were included in a linear regression model as predictors of treatment response.

RESULTS

Twenty-seven patients (87%) completed 8 weeks of treatment; 74% and 63% were responders at week 4 and 8, respectively. High S100B and low HDL-C levels at baseline were associated with better treatment response at both time points. Low CRP levels were correlated with better response at week 4. Multivariate analysis showed that high baseline S100B levels and low baseline HDL-C levels were good predictors of treatment response at week 4 (R2 = 0.457, P = .001), while S100B was at week 8 (R2 = 0.239, P = .011). Importantly, baseline S100B and HDL-C levels were not associated with depression severity and did not change over time with clinical improvement.

CONCLUSIONS

Serum S100B levels appear to be a useful biomarker of antidepressant response in MDD even when considering inflammatory and metabolic markers.

Time-Specific Associations of Tumor Necrosis Factor-α Levels and Polymorphisms (-850 C/T or -308 G/A) With Suicidal Ideation in Acute Coronary Syndrome Patients

Background: Considering the association of inflammation with suicide and acute coronary syndrome (ACS), we investigated the individual and interactive effects of serum tumor necrosis factor-alpha (sTNFα) levels and two polymorphisms (-850 C/T and -308 G/A) on suicidal ideation (SI) after ACS. Methods: The SI status using items on the Montgomery-Åsberg Depression Rating Scale (MADRS), related covariates including sociodemographic and clinical characteristics, sTNFα levels, and tumor necrosis factor-alpha (TNF-α) polymorphisms were evaluated in 969 patients within 2 weeks after ACS. Of the patients, 711 were evaluated 1 year later for SI. Multivariate logistic regression models were used to calculate individual and interactive associations after adjusting for the covariates. Results: Higher (vs. lower) sTNFα levels and the -850 C/T or T/T (vs. C/C) polymorphism were significantly associated with SI 2 weeks after ACS, while only higher sTNFα levels were significantly associated with SI after 1 year. Significant interactive effects were detected between sTNFα (higher) levels and the -850 C/T (C/C or C/T) polymorphism on SI 2 weeks after ACS and between the two (-850 CC or CT and -308 G/A or AA) polymorphisms on SI 1 year after ACS. Conclusions: The sTNFα level and two polymorphisms (-850C/T and -308 G/A), separately or in combination, could be time-specific biomarkers for SI in ACS. Focused interventions for ACS patients at risk of SI might reduce the suicidal burden in patients with ACS.