Major Depressive Disorder (MDD) is a prevalent mental health condition with a complex pathophysiology involving neuroinflammation, neurodegeneration, and disruptions in neuronal and glial cell function. Microglia, the innate immune cells of the central nervous system, release inflammatory cytokines in response to pathological changes associated with MDD. Damage-associated molecular patterns (DAMPs) act as alarms, triggering microglial activation and subsequent inflammatory cytokine release. This review examines the cellular mechanisms underlying MDD pathophysiology, focusing on the lipid-mediated modulation of neuroinflammation. We explore the intricate roles of microglia and astrocytes in propagating inflammatory cascades and discuss how these processes affect neuronal integrity at the cellular level. Central to our analysis are three key molecules: High Mobility Group Box 1 (HMGB1) and S100 Calcium Binding Protein β (S100β) as alarmins, and Neuron-Specific Enolase (NSE) as an indicator of neuronal stress. We present evidence from in vitro and ex vivo studies demonstrating how these molecules reflect and contribute to the neuroinflammatory milieu characteristic of MDD. The review then explores the potential of omega-3 polyunsaturated fatty acids (ω-3 PUFAs) as neuroinflammation modulators, examining their effects on microglial activation, cytokine production, and neuronal resilience in cellular models of depression. We critically analyze experimental data on how ω-3 PUFA supplementation influences the expression and release of HMGB1, S100β, and NSE in neuronal and glial cultures. By integrating findings from lipidomic and cellular neurobiology, this review aims to elucidate the mechanisms by which ω-3 PUFAs may exert their antidepressant effects through modulation of neuroinflammatory markers. These insights contribute to our understanding of lipid-mediated neuroprotection in MDD and may inform the development of targeted, lipid-based therapies for both depression and neurodegenerative disorders.

Objective: Omega-3 polyunsaturated fatty acids (n-3 PUFAs) have demonstrated protective effects in major depressive disorder (MDD) patients receiving antidepressant treatment. However, there have been a few double-blind randomized controlled trials focused on n-3 PUFAs as monotherapy in MDD, and the outcomes have been mixed. This study aimed to assess the clinical effects of n-3 PUFAs monotherapy in patients with MDD. Methods: A total of 60 patients with MDD participated in this 12-week double-blind randomized controlled trial. They were randomized to either the n-3 PUFAs group (n = 30; 3.2 g of eicosapentaenoic acid, EPA and docosahexaenoic acid, DHA per day) or the placebo group (n = 30; 3.2 g of soybean oil per day). The severity of depression was evaluated using the Hamilton Rating Scale for Depression (HRSD). Results: The n-3 PUFAs group had a significantly lower HRSD score compared with the placebo group at week 4 (p = 0.004), week 6 (p = 0.006), week 8 (p = 0.004), and week 12 (p = 0.01). The n-3 PUFAs group showed slightly higher rates for both remission (26.7% vs. 10%, p = 0.095) and response (23.3% vs. 6.7%, p = 0.145) compared with the placebo group at week 12, but these differences did not reach statistical significance. Conclusions: These findings suggested that monotherapy of n-3 PUFAs could improve depression and potentially serve as an alternative option for MDD patients.

From inadequate prior antidepressants that targeted monoamine neurotransmitter systems emerged the discovery of alternative drugs for depression. For instance, drugs targeted interleukin 6 receptor (IL6R) in inflammatory system. Genomic analysis-based drug repurposing using single nucleotide polymorphism (SNP) inclined a promising method for several diseases. However, none of the diseases was depression. Thus, we aimed to identify drug repurposing candidates for depression treatment by adopting a genomic-analysis-based approach. The 5885 SNPs obtained from the machine learning approach were annotated using HaploReg v4.1. Five sets of functional annotations were applied to determine the depression risk genes. The STRING database was used to expand the target genes and identify drug candidates from the DrugBank database. We validated the findings using the ClinicalTrial.gov and PubMed databases. Seven genes were observed to be strongly associated with depression (functional annotation score = 4). Interestingly, IL6R was auspicious as a target gene according to the validation outcome. We identified 20 drugs that were undergoing preclinical studies or clinical trials for depression. In addition, we identified sarilumab and satralizumab as drugs that exhibit strong potential for use in the treatment of depression. Our findings indicate that a genomic-analysis-based approach can facilitate the discovery of drugs that can be repurposed for treating depression.