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Major depressive disorder (MDD) is the most common mood disorder, and causes various mental, physical and cognitive symptoms. Clinicians diagnose MDD using multiple interviews and overall impression during the interviews, which makes MDD diagnosis highly subjective. To overcome this, we investigated novel protein biomarker for MDD. Serum from each subject were analyzed using nano liquid chromatography-triple time-of-flight mass spectrometry. We identified two proteins, zinc-alpha-2-glycoprotein (ZA2G) and keratin type II cytoskeletal 1 (K2C1), as final biomarkers. These biomarkers were downregulated during depression (p 0.05, AUC of ROC0.7). ZA2G is related to tryptophan metabolism, which is a main serotonin synthesis pathway. K2C1 is involved in the kinin-kallikrein system, which produces bradykinin, an anti-inflammatory mediator in the brain. Our results suggest that the two protein candidates are related to inflammation and that MDD is highly associated with inflammation. Finally, since all subjects in the two groups were taking antidepressants, our results suggest that the identified biomarkers could determine the presence or absence of illness and could be used to monitor therapeutic effects.

Major depressive disorder (MDD) is a common disorder involving depressive mood and decreased motivation. Due to its high heterogeneity, novel biomarkers are required to diagnose MDD. In this study, a proteomic method was used to identify a new MDD biomarker. Using sequential window acquisition of all theoretical mass spectra acquisitions and multiple reaction monitoring analysis via mass spectrometry, relative and absolute quantification of proteins in the sera was performed. The results of the relative quantitation by sequential window acquisition for all theoretical mass spectra data showed that seven proteins were significantly differently expressed between MDD patients and other patients with remission status. However, absolute quantification by multiple reaction monitoring analysis identified prothrombin as the only significantly upregulated protein in the depressive state compared to remission (p &lt, 0.05) and was, thus, subsequently selected as an MDD biomarker. The area under the curve for prothrombin was 0.66. Additionally, increased prothrombin/thrombin induced hyper-activation of platelets via activating protease-activated receptors, a feature associated with MDD, specifically, activated platelets secrete various molecules related to MDD, including brain-derived neurotropic factors and serotonin. Therefore, prothrombin is a potential screening, prognostic, and diagnostic marker for MDD.

Ischemic stroke is caused by blood clot formation and consequent vessel blockage. Proteomic approaches provide a cost-effective alternative to current diagnostic methods, including computerized tomography (CT) scans and magnetic resonance imaging (MRI). To identify diagnostic biomarkers associated with ischemic stroke risk factors, we performed individual proteomic analysis of serum taken from 20 healthy controls and 20 ischemic stroke patients. We then performed SWATH analysis, a data-independent method, to assess quantitative changes in protein expression between the two experimental conditions. Our analysis identified several candidate protein biomarkers, 11 of which were validated by multiple reaction monitoring (MRM) analysis as novel diagnostic biomarkers associated with ischemic stroke risk factors. Our study identifies new biomarkers associated with the risk factors and pathogenesis of ischemic stroke which, to the best of our knowledge, were previously unknown. These markers may be effective in not only the diagnosis but also the prevention and management of ischemic stroke.

Stroke has a high incidence rate and often leads to permanent disability, particularly if it is not treated promptly. However, no blood biomarkers for early diagnosis are available to date. Therefore, we sought to detect stroke-specific blood biomarkers by identifying proteins associated with the underlying coagulation mechanism, which accounts for more than 80% of all stroke cases. Protein profiling was performed using blood samples from 16 healthy controls and 18 patients who suffered a stroke as the discovery set. We identified upregulated proteins (> 1.5-fold change and p value