Depression is one of the most prevalent psychiatric disorders worldwide, with a steadily increasing incidence and complex, multifactorial pathophysiology. Beyond classical neurochemical mechanisms, growing evidence points to the role of systemic low-grade inflammation and immuno-metabolic disturbances in its development. Gut microbiota dysbiosis has emerged as a key factor linking metabolic, immune, and neuroendocrine pathways, potentially exacerbating neuroinflammation and contributing to the onset and progression of depressive symptoms. Immune activation, which is a result of gut dysbiosis, may play a crucial role in the pathogenesis of immuno-metabolic depression. Thyroid dysfunction appears to be an important, yet insufficiently understood component of this network. Thyroid hormones play a crucial role in regulating metabolism, immune responses, and central nervous system function. Alterations in thyroid function, even within subclinical ranges, have been associated with mood disturbances and may share common inflammatory and metabolic pathways with depression. Furthermore, emerging data suggest that gut microbiota may influence thyroid hormone metabolism, including deiodinase activity, linking dysbiosis with thyroid axis dysregulation. Despite these insights, the integrated interactions between thyroid function, gut microbiota, metabolic syndrome, and inflammation in depression remain largely unexplored. This review explores current evidence to highlight gaps in existing research and synthesizes current knowledge, aiming to clarify mechanisms underlying immuno-metabolic depression. Understanding these relationships may provide a rationale for redefining depression as an immuno-metabolic disorder and support the development of more integrative therapeutic strategies targeting not only the brain, but also the gut-thyroid axis.

The gut microbiota exhibits diurnal oscillations that are increasingly recognized as important modulators of host physiology, including brain function. Increasing evidence suggests that diurnal oscillations in microbial composition and activity may play a role in shaping cognitive performance. Microbiota and host circadian systems are tightly interconnected through feeding-fasting cycles, light-driven central clock signaling, and peripheral metabolic regulation, leading to coordinated rhythmicity across physiological systems. Disruptions to these rhythms, such as irregular eating patterns or circadian misalignment, have been associated with alterations in microbial profiles and impaired cognitive outcomes. Microbiota-derived metabolites, including short-chain fatty acids, tryptophan metabolites, and bile acids, serve as key signaling molecules that mediate communication along the gut-brain axis and influence processes such as memory, attention, and executive function. Emerging data support the existence of an integrated microbiota-circadian-cognition axis, in which microbial rhythmicity contributes to the regulation of neural and behavioral functions. Although current findings point to a meaningful association between microbiota rhythms and cognitive function, the evidence remains largely indirect and heterogeneous, showing that the time-related links between the microbiota and the brain are complex and not easy to explain. The aim of this narrative review is to synthesize current evidence on the relationships between microbiota rhythmicity, circadian regulation, and cognitive function, with a focus on possible mechanisms and potential clinical applications.

Background/Objectives: Despite the availability of multiple pharmacological treatment options, up to one-third of patients with depressive disorders fail to achieve adequate symptom relief following first-line antidepressant therapy, representing a major unmet clinical need. Fatty acids—including short-chain (SCFAs), medium-chain (MCFAs), and long-chain polyunsaturated fatty acids (PUFAs)—are increasingly implicated in depression pathogenesis through neuroinflammation, gut–brain axis signaling, and neurotransmitter metabolism, but their potential as predictors of antidepressant response remains largely unexplored. The primary aim is to evaluate whether baseline fatty acid profiles can predict pharmacological antidepressant treatment efficacy. The secondary objective is to assess the association between blood fatty acid profile and clinical presentation of depressive disorders. Methods: Sixty adults diagnosed with depressive disorders (ICD-11) at the initiation of a new antidepressant treatment will be recruited from psychiatric settings. Fasting blood samples collected at baseline will undergo gas chromatographic analysis of fatty acid methyl esters (FAMEs) and GC-MS quantification of SCFAs (acetic, propionic, and butyric acids). Clinical outcomes will be assessed at baseline and at 3, 6, and 12 weeks using the Beck Depression Inventory-II (BDI-II) and the Depression Anxiety Stress Scales (DASS-42). The primary endpoint is the change in BDI-II total score from baseline to week 6. Treatment response, defined as a ≥50% reduction in BDI-II total score at week 6, and remission, defined as a BDI-II score ≤12 at week 6, will be examined as secondary outcomes. Dietary habits, physical activity, quality of life, and anthropometric parameters will be collected as potential confounders. Discussion: This study is among the first prospective investigations to comprehensively characterize the circulating fatty acid spectrum as potential predictors of antidepressant outcomes. Findings may support identification of metabolic phenotypes of depression and contribute to personalized treatment strategies.