Proteomic Markers for Depression.

Major depressive disorder is a multifactorial disease, with molecular mechanisms not fully understood. A breakthrough could be reached with a panel of diagnostic biomarkers, which could be helpful to stratify patients and guide physicians to a better therapeutic choice, reducing the time between diagnostic and remission. This review brings the most recent works in proteomic biomarkers and highlights several potential proteins that could compose a panel of biomarkers to diagnostic and response to medication. These proteins are related to immune, inflammatory, and coagulatory systems and may also be linked to energy metabolism, oxidative stress, cell communication, and oligodendrogenesis.

Molecular Mechanisms Associated with Antidepressant Treatment on Major Depression.

Major depressive disorder (MDD) is a complex and multifactorial psychiatric disorder that causes serious health, social, and economic concerns worldwide. The main treatment of the symptoms is through antidepressant (AD) drugs. However, not all patients respond properly to these drugs. Omic sciences are widely used to analyze not only biomarkers for the AD response but also their molecular mechanism. In this review, we aimed to focus on omics data to better understand the molecular mechanisms involving AD effects on MDD. We consistently found, from preclinical to clinical data, that glutamatergic transmission, immune/inflammatory processes, energy metabolism, oxidative stress, and lipid metabolism were associated with traditional and potential new ADs. Despite efforts of studies investigating biomarkers of response to ADs, which could contribute to personalized treatment, there is no biomarker panel available for clinical application. From clinical genomic studies, we found that the main findings contribute to the development of pharmacogenomic tests for AD efficacy for each patient. Several studies pointed at DRD2, PXDNL, CACNA1E, and CACNA2D1 genes as potential targets for MDD treatment and the efficacy and rapid-antidepressant effect of ketamine. Finally, more in-depth studies of the molecular targets pointed here are needed to determine the clinical relevance and provide further evidence for precision MDD treatment.

Human Blood Plasma Investigation Employing 2D UPLC-UDMSE Data-Independent Acquisition Proteomics.

Proteomic tools are especially useful when it comes to investigating complex samples such as human blood plasma, in which protein quantities can span across up to ten orders of magnitude. Ultra definition mass spectrometry, in combination with two-dimensional liquid chromatography, provides better coverage of complex proteomes and allows for better control of collision energy, keeping the fragmentation benefits of high collision energy associated with drift time measurements from ion mobility separation. Here, we present a protocol to assist in the identification of proteins in human blood plasma and other similar samples with a large dynamic range.