A Pathway Proteomic Profile of Ischemic Stroke Survivors Reveals Innate Immune Dysfunction in Association with Mild Symptoms of Depression - A Pilot Study

2023 Sylvia Docker lecture: Ignite your passion, and connect, to make a difference

Together, we grow our profession of occupational therapy as we engage in understanding and addressing the issues that challenge the people we work with. In this Sylvia Docker Lecture, I will share the collective journeys of myself and other occupational therapists and health professionals who have undertaken (or are currently undertaking) their PhDs and are actively involved in research, to address these challenges. Together, we will explore three themes: understanding the WHY that ignites one's passion; living the journey-the EXPERIENCE; and making a difference-the IMPACT. Stories will be told through the lived experience of those engaged in research as currently enrolled PhD students, emerging researchers, and experienced researchers. These stories will capture the lived experience across individuals, and at different times in the research journey. Stories are summarised and captured using natural language processing. Topics are identified, concept maps visualised, and outputs interpreted in context of related theoretical models. Key topics identified include: the clinical and personal motivators that have ignited the passion in individuals; the value of connecting with others and growing networks; and how one's research has made a difference. The impact of discoveries and outcomes are highlighted, together with the importance of people and networks. Analysis of connections and synthesis over time revealed frequent and strong connections across themes, concepts and topics; with synthesising concepts of passion, networks, knowledge translation, opportunities, supervision and communication emerging and being shaped over time. These collective journeys provide inspiration and pathways to creative careers that have future potential in the growth of the profession of occupational therapy. It is recommended that each occupational therapist take the time to reflect on the 'why' that ignites your passion, your journey and how you can make a difference!

Proteomic advance of ischemic stroke: preclinical, clinical, and intervention

Ischemic stroke (IS) is the most common type of stroke and is characterized by high rates of mortality and long-term injury. The prediction and early diagnosis of IS are therefore crucial for optimal clinical intervention. Proteomics has provided important techniques for exploring protein markers associated with IS, but there has been no systematic evaluation and review of research that has used these techniques. Here, we review the differential proteins that have been found in cell- and animal- based studies and clinical trials of IS in the past 10 years; determine the key pathological proteins that have been identified in clinical trials; summarize the target proteins affected by interventions aimed at treating IS, with a focus on traditional Chinese medicine treatments. Overall, we clarify findings and problems that have been identified in recent proteomics research on IS and provide suggestions for improvements in this area. We also suggest areas that could be explored for determining the pathogenesis and developing interventions for IS.

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.

Bidirectional causal association between ischemic stroke and five mental disorders

OBJECTIVE

To explore the bidirectional causal association between ischemic stroke and five mental disorders from a genetic perspective using two-sample Mendelian randomization (TSMR).

METHODS

Single-nucleotide polymorphisms (SNPs) associated with ischemic stroke were obtained from the genome-wide association study (GWAS) database, and those closely related to the exposure phenotype and satisfying the three core assumptions of Mendelian randomization were selected as instrumental variables (IVs). The main TSMR analysis was conducted using the inverse variance-weighted (IVW) method, and the robustness of the results was assessed using the weighted median, weighted mode, and MR Egger methods. Heterogeneity test, pleiotropy test, and sensitivity analysis were also conducted to further ensure the accuracy and stability of the research results.

RESULTS

This study found a positive correlation between ischemic stroke and depression [IVW method (FEM): OR = 1.002, 95%CI: 1.000-1.003, P = 0.023<0.05], but no significant causal association with schizophrenia, bipolar disorder, insomnia, or anxiety (P > 0.05). Reverse TSMR analysis showed no causal association between depression, schizophrenia, bipolar disorder, insomnia, anxiety, and ischemic stroke (P > 0.05).

CONCLUSION

This study used TSMR to demonstrate from a genetic perspective that there is a positive correlation between ischemic stroke and depression, which increases the risk of depression. Proactive intervention for ischemic stroke might reduce the risk of depression.

Multi-omics research strategies in ischemic stroke: A multidimensional perspective

Ischemic stroke (IS) is a multifactorial and heterogeneous neurological disorder with high rate of death and long-term impairment. Despite years of studies, there are still no stroke biomarkers for clinical practice, and the molecular mechanisms of stroke remain largely unclear. The high-throughput omics approach provides new avenues for discovering biomarkers of IS and explaining its pathological mechanisms. However, single-omics approaches only provide a limited understanding of the biological pathways of diseases. The integration of multiple omics data means the simultaneous analysis of thousands of genes, RNAs, proteins and metabolites, revealing networks of interactions between multiple molecular levels. Integrated analysis of multi-omics approaches will provide helpful insights into stroke pathogenesis, therapeutic target identification and biomarker discovery. Here, we consider advances in genomics, transcriptomics, proteomics and metabolomics and outline their use in discovering the biomarkers and pathological mechanisms of IS. We then delineate strategies for achieving integration at the multi-omics level and discuss how integrative omics and systems biology can contribute to our understanding and management of IS.

Acute Routine Leukocyte and Neutrophil Counts Are Predictive of Poststroke Recovery at 3 and 12 Months Poststroke: An Exploratory Study

Background and Aims. White blood cell (WBC) and neutrophil counts (NC) are common markers of inflammation and neurological stroke damage and could be expected to predict poststroke outcomes. Objective. The aim of this study was to explore the prognostic value of early poststroke WBC and NC to predict cognition, mood, and disability outcomes at 3 and 12 months poststroke. Methods. Routine clinical analyses WBC and NC were collected at 3 time points in the first 4 days of hospitalization from 156 acute stroke patients. Correlations using hierarchical or ordinal regressions were explored between acute WBC and NC and functional recovery, depression, and cognition at 3 and 12 months poststroke, after covarying for age and baseline stroke severity. Results. We found significant increases in NC between <12 hours and 24 to 48 hours time points (P = .05). Hierarchical regressions, covaried for age and baseline stroke severity, found that 24 to 48 hours WBC (P = .05) and NC (P = .04) significantly predicted 3-month cognition scores. Similarly, 24 to 48 hours WBC (P = .05) and NC (P = .02) predicted cognition scores at 12 months. Increases in WBC and NC were predictive of increased cognition scores at both 3 and 12 months (positive recovery) though there were no significant associations between WBC and NC and disability or depression scores. Conclusions. Routine acute stroke clinical laboratory tests such as WBC and NC taken between 24 and 48 hours poststroke are predictive of cognition poststroke. It is interpreted that higher rapid immunological activation in the acute phase is an indicator for the trajectory of positive stroke recovery.

Exploring the Impact of Cerebrovascular Disease and Major Depression on Non-diseased Human Tissue Transcriptomes

Background

The development of complex diseases is contributed by the combination of multiple factors and complicated interactions between them. Inflammation has recently been associated with many complex diseases and may cause long-term damage to the human body. In this study, we examined whether two types of complex disease, cerebrovascular disease (CVD) or major depression (MD), systematically altered the transcriptomes of non-diseased human tissues and whether inflammation is linked to identifiable molecular signatures, using post-mortem samples from the Genotype-Tissue Expression (GTEx) project.

Results

Following a series of differential expression analyses, dozens to hundreds of differentially expressed genes (DEGs) were identified in multiple tissues between subjects with and without a history of CVD or MD. DEGs from these disease-associated tissues-the visceral adipose, tibial artery, caudate, and spinal cord for CVD; and the hypothalamus, putamen, and spinal cord for MD-were further analyzed for functional enrichment. Many pathways associated with immunological events were enriched in the upregulated DEGs of the CVD-associated tissues, as were the neurological and metabolic pathways in DEGs of the MD-associated tissues. Eight gene-tissue pairs were found to overlap with those prioritized by our transcriptome-wide association studies, indicating a potential genetic effect on gene expression for circulating cytokine phenotypes.

Conclusion

Cerebrovascular disease and major depression cause detectable changes in the gene expression of non-diseased tissues, suggesting that a possible long-term impact of diseases, lifestyles and environmental factors may together contribute to the appearance of "transcriptomic scars" on the human body. Furthermore, inflammation is probably one of the systemic and long-lasting effects of cerebrovascular events.

Hemispheric Difference of Regional Brain Function Exists in Patients With Acute Stroke in Different Cerebral Hemispheres: A Resting-State fMRI Study

Objective

To explore the different compensatory mechanisms of brain function between the patients with brain dysfunction after acute ischemic stroke (AIS) in the dominant hemisphere and the non-dominant hemisphere based on Resting-state Functional Magnetic Resonance Imaging (Rs-fMRI).

Methods

In this trial, 15 healthy subjects (HS) were used as blank controls. In total, 30 hemiplegic patients with middle cerebral artery acute infarction of different dominant hemispheres were divided into the dominant hemisphere group (DH) and the non-dominant hemisphere group (NDH), scanned by a 3.0 T MRI scanner, to obtain the amplitude of low-frequency fluctuations (ALFF) and regional homogeneity (ReHo) and compare the differences.

Results

Compared with the HS, increased ALFF values in the brain areas, such as the bilateral midbrain, were observed in DH. Meanwhile decreased ReHo values in the brain areas, such as the right postcentral gyrus (BA3), were also observed. Enhanced ALFF values in the brain areas, such as the left BA6, and enhanced ReHo values in the brain areas, such as the left precuneus, were observed in the NDH. The ALFF and ReHo values of the right BA9 and precentral gyrus were both increased. Compared with DH, the NDH group showed lower ALFF values in the left supplementary motor area and lower ReHo values in the right BA10.

Conclusion

After acute infarction in the middle cerebral artery of the dominant hemisphere, a compensation mechanism is triggered in brain areas of the ipsilateral cortex regulating motor-related pathways, while some brain areas related to cognition, sensation, and motor in the contralateral cortex are suppressed, and the connection with the peripheral brain regions is weakened. After acute infarction in the middle cerebral artery of the non-dominant hemisphere, compensatory activation appears in motor control-related brain areas of the dominant hemisphere. After acute middle cerebral artery infarction in the dominant hemisphere, compared with the non-dominant hemisphere, functional specificity in the bilateral supplementary motor area weakens. After acute middle cerebral artery infarction in different hemispheres, there are hemispheric differences in the compensatory mechanism of brain function.

Potential Genes and Mechanisms Linking Intracerebral Hemorrhage and Depression: A Bioinformatics-Based Study

Purpose

The purpose of this study was to investigate the potential pathogenic mechanisms of post-intracerebral hemorrhage depression.

Methods

Profiles of gene expression in brain tissue of patients with intracerebral hemorrhage (ICH) or depression were downloaded from the Gene Expression Omnibus (GEO) database. We analyzed differentially expressed genes (DEGs) for the two diseases separately. With these DEGs, we conducted an enrichment analysis based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) as well as cross-talk analysis, then we identified hub bridge genes using integrated bridge landscape analysis.

Results

We found 131 DEGs for interaction between ICH and depression. In the enrichment analysis, we found 55 GO terms and KEGG pathways involving interacting genes of ICH and depression, and 10 GO terms and 10 KEGG pathways most significantly related to cross-talk between ICH and depression. In the integrated bridge landscape analysis, we identified 20 hub bridge genes. In further analysis, we found that hub bridge genes HLA-A, HMOX1, and JUN related to endocytosis, cell adhesion, and phagosomes may exert their effects through the dopamine (DA) system and the serotonergic pathway post-ICH depression. HLA-A may play a role in the occurrence and development of ICH and depression through immune mediation and cell adhesion. HMOX1 and JUN may participate in the mechanism by interacting with HLA-A.

Conclusion

Through bioinformatics analysis, we identified potential hub bridge genes and pathways related to post-ICH depression. Our study provides references for further research on mechanisms on the pathogenesis of post-ICH depression.

Post-stroke depression: A 2020 updated review

BACKGROUND

Post-stroke depression (PSD) is common and associated with higher mortality, poorer recovery, more pronounced cognitive deficits, and lower quality of life than is stroke without depression. This manuscript will conduct an updated, comprehensive and clinically-useful review of the risk factors, pathophysiology, assessment, prevention, and treatment of PSD.

METHODS

This narrative review summarizes articles obtained on PubMed, Medline, EMBase, Google Scholar and the Cochrane Database. This review prioritized articles with a more robust level of evidence, such as original articles with longitudinal data and/or larger samples, randomized controlled trials, systematic reviews, and metaanalyses.

RESULTS

One hundred twenty-four articles were reviewed, of which 44 (35%) were published before 2016 and 80 (65%) that were published since 2016.

DISCUSSION

Rates of PSD range from 18 to 33%, yet it is vastly underdiagnosed and undertreated. Risk factors for PSD include female sex, history of psychiatric illness, large or multiple strokes, injuries in frontal/anterior areas or in the basal ganglia, stroke occurrence within the past year, poor social support, and pronounced disability. The pathophysiology of PSD is multifactorial and likely involves decreased levels of monoamines, abnormal neurotrophic response, increased inflammation with dysregulation of hypothalamic-pituitary-adrenal axis, and glutamate-mediated excitotoxicity. The evidence for preventive interventions for PSD is somewhat inconsistent and modest. The best treatment for PSD consists of the combination of pharmacological, psychosocial and stroke-focused interventions.

CONCLUSION

PSD is a common, treatable condition that is associated with several negative outcomes. Early detection and proper management are critical to obtain better outcomes in individuals with PSD.

Longitudinal Stroke Recovery Associated With Dysregulation of Complement System-A Proteomics Pathway Analysis

Currently the longitudinal proteomic profile of post-ischemic stroke recovery is relatively unknown with few well-accepted biomarkers or understanding of the biological systems that underpin recovery. We aimed to characterize plasma derived biological pathways associated with recovery during the first year post event using a discovery proteomics workflow coupled with a topological pathway systems biology approach. Blood samples (n = 180, ethylenediaminetetraacetic acid plasma) were collected from a subgroup of 60 first episode stroke survivors from the Australian START study at 3 timepoints: 3-7 days (T1), 3-months (T2) and 12-months (T3) post-stroke. Samples were analyzed by liquid chromatography mass spectrometry using label-free quantification (data available at ProteomeXchange with identifier PXD015006). Differential expression analysis revealed that 29 proteins between T1 and T2, and 33 proteins between T1 and T3 were significantly different, with 18 proteins commonly differentially expressed across the two time periods. Pathway analysis was conducted using Gene Graph Enrichment Analysis on both the Kyoto Encyclopedia of Genes and Genomes and Reactome databases. Pathway analysis revealed that the significantly differentiated proteins between T1 and T2 were consistently found to belong to the complement pathway. Further correlational analyses utilized to examine the changes in regulatory effects of proteins over time identified significant inhibitory regulation of clusterin on complement component 9. Longitudinal post-stroke blood proteomics profiles suggest that the alternative pathway of complement activation remains in a state of higher activation from 3-7 days to 3 months post-stroke, while simultaneously being regulated by clusterin and vitronectin. These findings also suggest that post-stroke induced sterile inflammation and immunosuppression could inhibit recovery within the 3-month window post-stroke.

Changes of Serum Melatonin, Interleukin-6, Homocysteine, and Complement C3 and C4 Levels in Patients With Depression

Objectives

Cytokine activation and low complement levels are common in depression patients. This study is aimed at investigating the clinical significance of changes in serum concentrations of melatonin (MT), interleukin-6 (IL-6), homocysteine (hcy), and complement C3 and C4 in depression patients and relationships of them with depression activity.

Methods

A total of 95 depression patients, including first-episode group (n = 43) and recurrent group (n = 52), and 45 age- and gender-matched healthy controls (HC) were recruited. Serum levels of MT, IL-6, hcy, C3, and C4 in all samples were measured by using enzyme-linked immunosorbent assay (ELISA), chemiluminescence method, enzyme circulation method, and immuno-scatter turbidimetric assay, respectively.

Results

The serum MT, IL-6, and hcy levels in the first-episode group (113.08 ± 5.06 pg/ml, 2.06 ± 0.12 ng/L, and 13.87 ± 0.45 μmol/L), and recurrent group (117.63 ± 4.63 pg/ml, 2.20 ± 0.12 ng/L, and 13.61 ± 0.46 μmol/L) were significantly higher than those in the control group (89.50 ± 5.10 pg/ml, 1.57 ± 0.06 ng/L, and 11.34 ± 0.40 μmol/L). The serum levels of C3 in the first-episode group (0.95 ± 0.02 ng/L) were significantly lower than those in the recurrent group (1.05 ± 0.03 ng/L) and control group (1.12 ± 0.03 ng/L). There was no significant difference in serum C4 level between each group.

Conclusion

These results suggest that higher serum MT, IL-6, and hcy levels were correlated with pathogenesis of depression.

Establishing molecular signatures of stroke focusing on omic approaches: a narrative review

Stroke or 'brain attack' is considered to be the major cause of mortality and morbidity worldwide after myocardial infraction. Inspite of the years of research and clinical practice, the pathogenesis of stroke still remains incompletely understood. Omics approaches not only enable the description of a huge number of molecular platforms but also have a potential to recognize new factors associated with various complex disorders including stroke. The most significant development among all other omics technologies over the recent years has been seen by genomics which is a powerful tool for exploring the genetic architecture of stroke. Genomics has decisively established itself in stroke research and by now wealth of data has been generated providing new insights into the physiology and pathophysiology of stroke. However, the efficacy of genomic data is restricted to risk prediction only. Omics approaches not only enable the description of a huge number of molecular platforms but also have a potential to recognize new factors associated with various complex disorders including stroke. The data generated by omics technologies enables clinicians to provide detailed insight into the makeup of stroke in individual patients, which will further help in developing diagnostic procedures to direct therapies. Present review has been compiled with an aim to understand the potential of integrated omics approach to help in characterization of mechanisms leading to stroke, to predict the patient risk of getting stroke by analyzing signature biomarkers and to develop targeted therapeutic strategies.

Proteomic identification of galectin-11 and -14 ligands from Fasciola hepatica

Fasciola hepatica is a globally distributed zoonotic trematode that causes fasciolosis in livestock, wildlife, ruminants and humans. Fasciolosis causes a significant economic impact on the agricultural sector and affects human health. Due to the increasing prevalence of triclabendazole resistance in F. hepatica, alternative treatment methods are required. Many protein antigens have been trialled as vaccine candidates with low success, however, the tegument of F. hepatica is highly glycosylated and the parasite-derived glycoconjugate molecules have been identified as an important mediator in host-parasite interactions and as prime targets for the host immune system. Galectin-11 (LGALS-11) and galectin-14 (LGALS-14) are two ruminant-specific glycan-binding proteins, showing upregulation in the bile duct of sheep infected with F. hepatica, which are believed to mediate host-parasite interaction and innate immunity against internal parasites. For the first known time, this study presents the ligand profile of whole worm and tegument extracts of F. hepatica that interacted with immobilised LGALS-11 and LGALS-14. LGALS-14 interacted with a total of 255 F. hepatica proteins. The protein which had the greatest interaction was identified as an uncharacterised protein which contained a C-type lectin domain. Many of the other proteins identified were previously trialled vaccine candidates including glutathione S-transferase, paramyosin, cathepsin L, cathepsin B, fatty acid binding protein and leucine aminopeptidase. In comparison to LGALS-14, LGALS-11 interacted with only 49 F. hepatica proteins and it appears to have a much smaller number of binding partners in F. hepatica. This is, to our knowledge, the first time host-specific lectins have been used for the enrichment of F. hepatica glycoproteins and this study has identified a number of glycoproteins that play critical roles in host-parasite interactions which have the potential to be novel vaccine candidates.

Global brain inflammation in stroke

Stroke, including acute ischaemic stroke and intracerebral haemorrhage, results in neuronal cell death and the release of factors such as damage-associated molecular patterns (DAMPs) that elicit localised inflammation in the injured brain region. Such focal brain inflammation aggravates secondary brain injury by exacerbating blood-brain barrier damage, microvascular failure, brain oedema, oxidative stress, and by directly inducing neuronal cell death. In addition to inflammation localised to the injured brain region, a growing body of evidence suggests that inflammatory responses after a stroke occur and persist throughout the entire brain. Global brain inflammation might continuously shape the evolving pathology after a stroke and affect the patients' long-term neurological outcome. Future efforts towards understanding the mechanisms governing the emergence of so-called global brain inflammation would facilitate modulation of this inflammation as a potential therapeutic strategy for stroke.

Fatigue in primary Sjögren's syndrome: A proteomic pilot study of cerebrospinal fluid

Objectives:

Fatigue is a frequent and often disabling phenomenon that occurs in patients with chronic inflammatory and immunological diseases, and the underlying biological mechanisms are largely unknown. Because fatigue is generated in the brain, we aimed to investigate cerebrospinal fluid and search for molecules that participate in the pathophysiology of fatigue processes.

Methods:

A label-free shotgun proteomics approach was applied to analyze the cerebrospinal fluid proteome of 20 patients with primary Sjögren’s syndrome. Fatigue was measured with the fatigue visual analog scale.

Results:

A total of 828 proteins were identified and the 15 top discriminatory proteins between patients with high and low fatigue were selected. Among these were apolipoprotein A4, hemopexin, pigment epithelium-derived factor, secretogranin-1, secretogranin-3, selenium-binding protein 1, and complement factor B.

Conclusion:

Most of the discriminatory proteins have important roles in regulation of innate immunity, cellular stress defense, and/or functions in the central nervous system. These proteins and their interacting protein networks may therefore have central roles in the generation and regulation of fatigue, and the findings contribute with evidence to the concept of fatigue as a biological phenomenon signaled through specific molecular pathways.

Distinct plasma proteomic changes in male and female African American stroke patients

BACKGROUND

Stroke occurs more often and results in more severe brain injury in African Americans than in Caucasians. The former also exhibit different responses to thrombolytic therapy than the latter do. There is an imminent need for stroke biomarkers for African Americans, who have been underrepresented in biomarker research for stroke diagnosis and prognosis. Proteomics offers sources for protein biomarkers that are not available by other Omics approaches. In this pilot study, plasma proteomes of African American stroke patients were analyzed and compared to that of hypertensive, non-stroke controls.

METHODS

Plasma samples were prepared from whole blood specimens that were collected from stroke patients admitted to Grady Memorial Hospital in Atlanta, and their age- and sex-matched, hypertensive controls from the outpatient clinic. Samples were pooled according to patient groups and sex. Plasma proteins were analyzed with quantitative mass spectrometry. The identified and quantified proteins were compared between stroke and control patients of each sex. Proteins that showed changes in abundances in stroke patients were further analyzed with the assistance of bioinformatics tools for their known biological functions or potential implications in stroke.

RESULTS

A total of 128 annotated proteins were identified. Results of bioinformatic analysis of plasma proteins whose levels were increased in stroke patients showed, as expected, their association with blood coagulation and inflammation processes. Interestingly, a number of proteins showed different or even opposing changes in male and female stroke patients, notably those involved in IL-4 and IL-6 signaling, complement activation, and blood coagulation disorders. For a few proteins that were increased in female but unchanged or decreased in male stroke patients, an association with fibromuscular dysplasia was recognized.

CONCLUSION

Plasma proteins that differ in quantities between stroke patients and controls were readily detected using a simple proteomic approach. Sex-dependent changes and changes that have not been reported for African American stroke patients offer potentially novel biomarkers for stroke in this underserved population.

Effect of Inflammation on the Process of Stroke Rehabilitation and Poststroke Depression

A considerable body of evidence has shown that inflammation plays an important role in the process of stroke rehabilitation and development of poststroke depression (PSD). However, the specific molecular and cellular mechanisms involved remain unclear. In this review, we summarize how neuroinflammation affects stroke rehabilitation and PSD. We mainly focus on the immune/inflammatory response, involving astrocytes, microglia, monocyte-derived macrophages, cytokines (tumor necrosis factor alpha, interleukin 1), and microRNAs (microRNA-124, microRNA 133b). This review provides new insights into the effect of inflammation on the process of stroke rehabilitation and PSD and potentially offer new therapeutic targets of stroke and PSD.

Neuro-Immune Hemostasis: Homeostasis and Diseases in the Central Nervous System

Coagulation and the immune system interact in several physiological and pathological conditions, including tissue repair, host defense, and homeostatic maintenance. This network plays a key role in diseases of the central nervous system (CNS) by involving several cells (CNS resident cells, platelets, endothelium, and leukocytes) and molecular pathways (protease activity, complement factors, platelet granule content). Endothelial damage prompts platelet activation and the coagulation cascade as the first physiological step to support the rescue of damaged tissues, a flawed rescuing system ultimately producing neuroinflammation. Leukocytes, platelets, and endothelial cells are sensitive to the damage and indeed can release or respond to chemokines and cytokines (platelet factor 4, CXCL4, TNF, interleukins), and growth factors (including platelet-derived growth factor, vascular endothelial growth factor, and brain-derived neurotrophic factor) with platelet activation, change in capillary permeability, migration or differentiation of leukocytes. Thrombin, plasmin, activated complement factors and matrix metalloproteinase-1 (MMP-1), furthermore, activate intracellular transduction through complement or protease-activated receptors. Impairment of the neuro-immune hemostasis network induces acute or chronic CNS pathologies related to the neurovascular unit, either directly or by the systemic activation of its main steps. Neurons, glial cells (astrocytes and microglia) and the extracellular matrix play a crucial function in a “tetrapartite” synaptic model. Taking into account the neurovascular unit, in this review we thoroughly analyzed the influence of neuro-immune hemostasis on these five elements acting as a functional unit (“pentapartite” synapse) in the adaptive and maladaptive plasticity and discuss the relevance of these events in inflammatory, cerebrovascular, Alzheimer, neoplastic and psychiatric diseases. Finally, based on the solid reviewed data, we hypothesize a model of neuro-immune hemostatic network based on protein–protein interactions. In addition, we propose that, to better understand and favor the maintenance of adaptive plasticity, it would be useful to construct predictive molecular models, able to enlighten the regulating logic of the complex molecular network, which belongs to different cellular domains. A modeling approach would help to define how nodes of the network interact with basic cellular functions, such as mitochondrial metabolism, autophagy or apoptosis. It is expected that dynamic systems biology models might help to elucidate the fine structure of molecular events generated by blood coagulation and neuro-immune responses in several CNS diseases, thereby opening the way to more effective treatments.

Poststroke Depression Biomarkers: A Narrative Review

Poststroke depression (PSD) is the most prevalent psychiatric disorder after stroke, which is independently correlated with negative clinical outcome. The identification of specific biomarkers could help to increase the sensitivity of PSD diagnosis and elucidate its pathophysiological mechanisms. The aim of current study was to review and summarize literature exploring potential biomarkers for PSD diagnosis. The PubMed database was searched for papers published in English from October 1977 to December 2017, 90 of which met inclusion criteria for clinical studies related to PSD biomarkers. PSD biomarkers were subdivided into neuroimaging, molecular, and neurophysiological. Some of them could be recommended to support PSD diagnosing. According to the data, lesions affecting the frontal-subcortical circles of mood regulation (prefrontal cortex, basal nuclei, and thalamus) predominantly in the left hemisphere can be considered as neuroimaging markers and predictors for PSD for at least 1 year after stroke. Additional pontine and lobar cerebral microbleeds in acute stroke patients, as well as severe microvascular lesions of the brain, increase the likelihood of PSD. The following molecular candidates can help to differentiate PSD patients from non-depressed stroke subjects: decreased serum BDNF concentrations; increased early markers of inflammation (high-sensitivity C-reactive protein, ferritin, neopterin, and glutamate), serum pro-inflammatory cytokines (TNF-α, IL-1β, IL-6, IL-18, IFN-γ), as well as pro-inflammatory/anti-inflammatory ratios (TNF-α/IL-10, IL-1β/IL-10, IL-6/IL-10, IL-18/IL-10, IFN-γ/IL-10); lowered complement expression; decreased serum vitamin D levels; hypercortisolemia and blunted cortisol awakening response; S/S 5-HTTLPR, STin2 9/12, and 12/12 genotypes of the serotonin transporter gene SLC6A4, 5-HTR2a 1438 A/A, and BDNF met/met genotypes; higher SLC6A4 promoter and BDNF promoter methylation status. Neurophysiological markers of PSD, that reflect a violation of perception and cognitive processing, are the elongation of the latency of N200, P300, and N400, as well as the decrease in the P300 and N400 amplitude of the event-related potentials. The selected panel of biomarkers may be useful for paraclinical underpinning of PSD diagnosis, clarifying various aspects of its multifactorial pathogenesis, optimizing therapeutic interventions, and assessing treatment effectiveness.

Direct Assessment of Plasma/Serum Sample Quality for Proteomics Biomarker Investigation

Blood proteome analysis for biomarker discovery represents one of the most challenging tasks to be achieved through clinical proteomics due to the sample complexity, such as the extreme heterogeneity of proteins in very dynamic concentrations, and to the observation of proper sampling and storage conditions. Quantitative and qualitative proteomics profiling of plasma and serum could be useful both for the early detection of diseases and for the evaluation of pathological status. Two main sources of variability can affect the precision and accuracy of the quantitative experiments designed for biomarker discovery and validation. These sources are divided into two categories, pre-analytical and analytical, and are often ignored; however, they can contribute to consistent errors and misunderstanding in biomarker research. In this chapter, we review critical pre-analytical and analytical variables that can influence quantitative proteomics. According to guidelines accepted by proteomics community, we propose some recommendations and strategies for a proper proteomics analysis addressed to biomarker studies.

Proteomic identification of galectin-11 and 14 ligands from Haemonchus contortus

Haemonchus contortus is the most pathogenic nematode of small ruminants. Infection in sheep and goats results in anaemia that decreases animal productivity and can ultimately cause death. The involvement of ruminant-specific galectin-11 (LGALS-11) and galectin-14 (LGALS-14) has been postulated to play important roles in protective immune responses against parasitic infection; however, their ligands are unknown. In the current study, LGALS-11 and LGALS-14 ligands in H. contortus were identified from larval (L4) and adult parasitic stages extracts using immobilised LGALS-11 and LGALS-14 affinity column chromatography and mass spectrometry. Both LGALS-11 and LGALS-14 bound more putative protein targets in the adult stage of H. contortus (43 proteins) when compared to the larval stage (two proteins). Of the 43 proteins identified in the adult stage, 34 and 35 proteins were bound by LGALS-11 and LGALS-14, respectively, with 26 proteins binding to both galectins. Interestingly, hematophagous stage-specific sperm-coating protein and zinc metalloprotease (M13), which are known vaccine candidates, were identified as putative ligands of both LGALS-11 and LGALS-14. The identification of glycoproteins of H. contortus by LGALS-11 and LGALS-14 provide new insights into host-parasite interactions and the potential for developing new interventions.

Repetitive transcranial magnetic stimulation for the treatment of post-stroke depression: A systematic review and meta-analysis of randomized controlled clinical trials

BACKGROUND

Every year, more than fifteen million people worldwide experience a stroke, nearly 30% of stroke survivors are likely to experience post-stroke depression (PSD). Repetitive transcranial magnetic stimulation (rTMS) is one of the emerging techniques which assist in targeting rehabilitation after stroke. Although deterioration of PSD greatly affects the recovery and quality of life of stroke sufferers, the effect of rTMS therapy has not been systematically studied.

OBJECTIVE

A systematic review and meta-analysis was conducted to determine the effect of rTMS on PSD.

METHODS

We carried out a systematic review and meta-analysis of randomized controlled trials (RCTs) of rTMS for the treatment of PSD. Primary outcome was severity of depression measured by the Hamilton Depression Rating Scale (HAMD). Secondary outcomes were response rates, remission rates, stroke severity and ability to perform daily activities.

RESULTS

22 RCTs studies (n=1764 patients) were included. The results demonstrated that rTMS was beneficial on PSD using three scales: HAMD (MD=-6.09, 95% CI: -7.74, -4.45, P<0.001); response rates (OR=3.46, 95% CI: 2.52, 4.76, P<0.00001); remission rates (OR 0.99, 95% CI: 0.56, 1.75, P<0.00001); National Institutes of Health Stroke Scale (NIHSS) (MD=-2.74, 95% CI: -3.33, -2.15, P<0.001); Activities of daily living (ADL) (SMD=-1.20, 95% CI: 0.68, 1.72, P<0.001); Montgomery-Asberg Depression Scale (MARDE) (MD=-6.21; 95% CI: -9.34, -3.08; P=0.0001); CONCLUSION: In present meta-analysis, the positive findings suggest rTMS has beneficial effects on PSD. However, those findings should be treated with caution because of heterogeneity and potential biases.