Characterizing fatigue phenotypes with other symptoms and clinically relevant outcomes among people with multiple sclerosis.

PURPOSE: Fatigue is a common symptom of multiple sclerosis (MS) and can adversely affect all aspect of quality of life. The etiology of fatigue remains unclear, and its treatments are suboptimal. Characterizing the phenotypes of fatigued persons with MS may help advance research on fatigue's etiology and identify ways to personalize fatigue interventions to improve quality of life. The purpose of this study was to identify fatigue phenotypes; examine phenotype stability overtime; and characterize phenotypes by health and function, social and environmental determinants, psychosocial factors, and engagement in healthy behaviors. METHODS: We conducted a longitudinal study over a 3-month period with 289 fatigued participants with MS. To identify fatigue phenotypes and determine transition probabilities, we used latent profile and transition analyses with valid self-report measures of mental and physical fatigue severity, the mental and physical impact of fatigue, depression, anxiety, and sleep quality. We used ANOVAs and effect sizes to characterize differences among phenotypes. RESULTS: The best fitting model included six subgroups of participants: Mild Phenotype, Mild-to-Moderate Phenotype, Moderate-to-Severe Phenotype, Severe Phenotype, Fatigue-dominant Phenotype, and Mental Health-dominant Phenotype. The transition analysis indicated that phenotypic membership was highly stable. Variables with a large eta squared effect size included environmental barriers, self-efficacy, and fatigue catastrophizing. CONCLUSION: These results indicate that the magnitude of fatigue experienced may be more important to consider than the type of fatigue when characterizing fatigue phenotypes. Future research should explore whether tailoring interventions to environmental barriers, self-efficacy, and fatigue catastrophizing reduce the likelihood of transitioning to a more severe phenotype.

Predictors of fatigue self-management behaviors in adults with multiple sclerosis.

BACKGROUND: Fatigue is one of the most common and disabling symptoms in people with multiple sclerosis (MS). Fatigue self-management behaviors may be effective in reducing the impact of fatigue in people with MS. However, few studies have examined the factors that influence engagement in fatigue self-management behaviors. OBJECTIVE: Identify factors that directly and indirectly influence fatigue self-management behaviors. METHODS: Participants with MS (n = 287) completed online questionnaires at baseline and 6-weeks. Guided by the Self- and Family Management Framework, we examined the influence of health status, resources and environment, healthcare utilization, and self-management processes on fatigue self-management behaviors at 6-weeks. Multiple regression and path analyses were conducted. RESULTS: The final regression model variables accounted for 41.58% of the variance in fatigue self-management behaviors, which included outcome expectations (ß= 0.287), disability (ß= 0.265), environmental barriers (ß= 0.188), self-efficacy (ß= 0.153), symptom severity (ß= 0.113), living in an urban community (ß= -0.108), and living alone (ß= 0.103). Path analysis indicated that outcome expectations may mediate the relationship between disability levels and fatigue self-management behavior. CONCLUSIONS: Health status (i.e., disability and symptom severity), environmental factors (e.g., living situation), and self-management processes (i.e., self-efficacy and outcome expectations) may play an important role in influencing engagement in fatigue self-management behaviors.

Large-scale informatic analysis to algorithmically identify blood biomarkers of neurological damage.

The identification of precision blood biomarkers which can accurately indicate damage to brain tissue could yield molecular diagnostics with the potential to improve how we detect and treat neurological pathologies. However, a majority of candidate blood biomarkers for neurological damage that are studied today are proteins which were arbitrarily proposed several decades before the advent of high-throughput omic techniques, and it is unclear whether they represent the best possible targets relative to the remainder of the human proteome. Here, we leveraged mRNA expression data generated from nearly 12,000 human specimens to algorithmically evaluate over 17,000 protein-coding genes in terms of their potential to produce blood biomarkers for neurological damage based on their expression profiles both across the body and within the brain. The circulating levels of proteins associated with the top-ranked genes were then measured in blood sampled from a diverse cohort of patients diagnosed with a variety of acute and chronic neurological disorders, including ischemic stroke, hemorrhagic stroke, traumatic brain injury, Alzheimer's disease, and multiple sclerosis, and evaluated for their diagnostic performance. Our analysis identifies several previously unexplored candidate blood biomarkers of neurological damage with possible clinical utility, many of which whose presence in blood is likely linked to specific cell-level pathologic processes. Furthermore, our findings also suggest that many frequently cited previously proposed blood biomarkers exhibit expression profiles which could limit their diagnostic efficacy.

Analysis of Early Stroke-induced Changes in Circulating Leukocyte Counts using Transcriptomic Deconvolution.

Growing evidence suggests that stroke alters the phenotype of the peripheral immune system; better characterization of this response could provide new insights into stroke pathophysiology. In this investigation, we employed a deconvolution approach to informatically infer the cellular composition of the circulating leukocyte pool at multiple timepoints following stroke onset based on whole blood mRNA expression. Microarray data generated from the peripheral blood of 23 cardiovascular disease controls and 23 ischemic stroke patients at 3, 5, and 24 hours post-symptom onset were obtained from a public repository. Transcriptomic deconvolution was used to estimate the relative counts of nine leukocyte populations based on the expression of cell-specific transcripts, and cell counts were compared between groups across timepoints. Inferred counts of lymphoid cell populations including B-cells, CD4+ T-cells, CD8+ T-cells, γδ T-cells, and NK-cells were significantly lower in stroke samples relative to control samples. With respect to myeloid cell populations, inferred counts of neutrophils and monocytes were significantly higher in stroke samples compared to control samples, however inferred counts of eosinophils and dendritic cells were significantly lower. These collective differences were most dramatic in samples collected at 5 and 24 hours post-symptom onset. Findings were subsequently confirmed in a second dataset generated from an independent population of 24 controls and 39 ischemic stroke patients. Collectively, these results offer a comprehensive picture of the early stroke-induced changes to the complexion of the circulating leukocyte pool, and provide some of the first evidence that stroke triggers an acute decrease in eosinophil counts.

Prognostic impact of bcl-2 expression on advanced nasopharyngeal carcinoma.

BACKGROUND: Our aim was to evaluate the prognostic impact of bcl-2 expression on patients with advanced nasopharyngeal carcinoma (NPC). METHODS: One hundred five patients with advanced NPC treated with high-dose radiotherapy were included. The relationship between bcl-2 expression, TNM stage, and disease-specific survival was analyzed. RESULTS: Within the same stage III and IV, patients with negative bcl-2 expression had better disease-free survival. The disease-free survival of patients with stage IV NPC with negative bcl-2 expression was paradoxically better than that of patients with stage III NPC with positive bcl-2 expression. In the advanced NPC, the disease-free survival of patients with stage III cancer was better than that of patients with stage IV cancer (p = .06); in contrast, patients with bcl-2-positive tumors had a worse disease-free 5-year survival (p = .02). The Cox regression model revealed that only bcl-2 expression was statistically significant (p = .03). CONCLUSION: In advanced staged NPC, bcl-2 expression represented an important prognostic factor.

Disturbance of circadian gene expression in hepatocellular carcinoma.

Circadian rhythm plays an important role in the regulation of digestive system. The human circadian rhythm is controlled by at least nine circadian genes. The aims of this study are to understand the expression of the circadian genes between hepatocellular carcinoma tissues and nontumor tissues, and to explore the possible mechanism(s) contributing to the difference. We analyzed differential expression of the 9 circadian genes in 46 hepatocellular carcinoma and paired noncancerous tissues by real-time quantitative RT-PCR and immunohistochemical detection. We also tested the possible regulatory mechanism(s) by direct sequencing and methylation PCR analysis. Our results showed that decreased expression levels of PER1, PER2, PER3, CRY2, and TIM in hepatocellular carcinomas were observed. Decreased-expression of these genes was not caused by genetic mutations, but by several factors, such as promoter methylation, overexpression of EZH2 or other factors. The down expression of more circadian genes may result in disturbance of cell cycle, and it is correlated with the tumor size. Downregulation of circadian genes results in disturbance of circadian rhythm in hepatocellular carcinoma which may disrupt the control of the central pacemaker and benefit selective survival of cancerous cells and promote carcinogenesis.

Expression of CD80 and CD86 costimulatory molecules are potential markers for better survival in nasopharyngeal carcinoma.

BACKGROUND: B7 Costimulatory signal is essential to trigger T-cell activation upon the recognition of tumor antigens. This study examined the expression of B7-1 (CD80) and B7-2 (CD86) costimulatory molecules along with HLA-DR and the presence of infiltrating lymphocytes and dendritic cells to assess their significance in patients with nasopharyngeal carcinoma (NPC). METHODS: Expression of CD80, CD86, HLA-DR, S-100 protein and the presence of infiltrating lymphocytes and follicular dendritic reticulum cells were immunohistochemically examined on the paraffin-embedded tissue blocks from newly diagnosed NPC patients (n = 50). The results were correlated with clinical outcome of patients. RESULTS: CD80 and CD86 were each expressed in 10 of 50 cases in which they co-expressed in 9 cases. Univariate analysis revealed that patients with CD80/CD86 expression had significantly better overall survival than those without it (P = 0.017), but after adjustment for stage, nodal status, and treatment, the expression of CD80/CD86 did not significantly correlate with overall survival. Expression of HLA-DR and the presence of infiltrating lymphocytes and dendritic cells did not appear to have impact on the survival of patients. CONCLUSION: Expression of CD80 and CD86 costimulatory molecules appears to be a marker of better survival in patient with NPC.

Expression of p53 protein and primary tumour volume in patients with nasopharyngeal carcinoma.

OBJECTIVE: To investigate the relationship of p53 protein expression and primary tumour volume in patients with nasopharyngeal carcinoma. DESIGN: Retrospective study. SETTING: Tertiary care centre. METHOD: Forty-two newly diagnosed patients participated in the study. MAIN OUTCOME MEASURES: The relationship between p53 status, TNM stage, and computed tomography-derived primary tumour volume. RESULTS: In patients with high p53 stains, the tumour volume was larger (p = .03). p53 was found to be independent of clinical stage (p = .84). CONCLUSION: There is a positive correlation between primary tumour volume and p53 status.