Early Post-stroke Depressive Symptoms are Associated with Low Peripheral Levels of Soluble Triggering Receptor Expressed on Myeloid Cells-1 (sTREM-1) and Glial Cell-derived Neurotrophic Factor (GDNF)

Machine learning models of plasma proteomic data predict mood in chronic stroke and tie it to aberrant peripheral immune responses

Post-stroke depression is common, long-lasting and associated with severe morbidity and death, but mechanisms are not well-understood. We used a broad proteomics panel and developed a machine learning algorithm to determine whether plasma protein data can predict mood in people with chronic stroke, and to identify proteins and pathways associated with mood. We used Olink to measure 1,196 plasma proteins in 85 participants aged 25 and older who were between 5 months and 9 years after ischemic stroke. Mood was assessed with the Stroke Impact Scale mood questionnaire (SIS3). Machine learning multivariable regression models were constructed to estimate SIS3 using proteomics data, age, and time since stroke. We also dichotomized participants into better mood (SIS3 > 63) or worse mood (SIS3 ≤ 63) and analyzed candidate proteins. Machine learning models verified that there is indeed a relationship between plasma proteomic data and mood in chronic stroke, with the most accurate prediction of mood occurring when we add age and time since stroke. At the individual protein level, no single protein or set of proteins predicts mood. But by using univariate analyses of the proteins most highly associated with mood we produced a model of chronic post-stroke depression. We utilized the fact that this list contained many proteins that are also implicated in major depression. Also, over 80% of immune proteins that correlate with mood were higher with worse mood, implicating a broadly overactive immune system in chronic post-stroke depression. Finally, we used a comprehensive literature review of major depression and acute post-stroke depression. We propose that in chronic post-stroke depression there is over-activation of the immune response that then triggers changes in serotonin activity and neuronal plasticity leading to depressed mood.

Inhibition of TREM-1 Ameliorates Lipopolysaccharide-induced Depressive-like Behaviors by Alleviating Neuroinflammation in the PFC via PI3K/Akt Signaling Pathway

Neuroinflammation is closely related to depression and is a key pathophysiological process of depression. Triggering receptor expressed on myeloid cells 1 (TREM-1) has been proven to exert proinflammatory effects in various diseases. However, the role of TREM-1 in depression has not been elucidated. Thus, we hypothesized that TREM-1 inhibition might have protective effects in depression. Here, lipopolysaccharide (LPS) was used to induce depressive-like behaviors in mice, LP17 was treated to inhibit TREM-1, and LY294002 was administrated to inhibit phosphatidylinositol 3-kinase (PI3K) which is one of the downstream of TREM-1. Physical and neurobehavioral tests, Western blot analysis, and immunofluorescence staining were performed in this study. We found that LPS caused significant depressive-like behaviors in mice, including body weight decline, anodynia (sucrose preference decrease), lack of locomotor activity, and desperation in tail suspension test (TST) and forced swimming test (FST). Next, we revealed that TREM-1 was expressed on microglia, neurons, and astrocytes in the prefrontal cortex (PFC) after LPS administration. TREM-1 inhibition by LP17 suppressed the expression of TREM-1 in the PFC. In addition, LP17 could alleviate neuroinflammation and microglial activation in the PFC. Meanwhile, LP17 could prevent damage of LPS to neuronal primary cilia and neuronal activity. Finally, we revealed that PI3K/Akt might exert crucial role in the protective effects of TREM-1 inhibition to depressive-like behaviors induced by LPS. Taken together, TREM-1 inhibition by LP17 could alleviate depressive-like behaviors induced by LPS by mitigating neuroinflammation in the PFC via PI3K/Akt signaling pathway. Finally, we demonstrated that TREM-1 might be a promising therapeutic target for treatment of depression.

The role of triggering receptor expressed on myeloid cells-1 (TREM-1) in central nervous system diseases

Triggering receptor expressed on myeloid cells-1 (TREM-1) is a member of the immunoglobulin superfamily and is mainly expressed on the surface of myeloid cells such as monocytes, macrophages, and neutrophils. It plays an important role in the triggering and amplification of inflammatory responses, and it is involved in the development of various infectious and non-infectious diseases, autoimmune diseases, and cancers. In recent years, TREM-1 has also been found to participate in the pathological processes of several central nervous system (CNS) diseases. Targeting TREM-1 may be a promising strategy for treating these diseases. This paper aims to characterize TREM-1 in terms of its structure, signaling pathway, expression, regulation, ligands and pathophysiological role in CNS diseases.