Comorbidities of epilepsy: current concepts and future perspectives

The burden of comorbidity in people with epilepsy is high. Several diseases, including depression, anxiety, dementia, migraine, heart disease, peptic ulcers, and arthritis are up to eight times more common in people with epilepsy than in the general population. Several mechanisms explain how epilepsy and comorbidities are associated, including shared risk factors and bidirectional relations. There is a pressing need for new and validated screening instruments and guidelines to help with the early detection and treatment of comorbid conditions. Preliminary evidence suggests that some conditions, such as depression and migraine, negatively affect seizure outcome and quality of life. Further investigation is needed to explore these relations and the effects of targeted interventions. Future advances in the investigation of the comorbidities of epilepsy will strengthen our understanding of epilepsy and could play an important part in stratification for genetic studies

Transcriptome Profiling of Whole Blood Cells Identifies PLEK2 and C1QB in Human Melanoma

Developing analytical methodologies to identify biomarkers in easily accessible body fluids is highly valuable for the early diagnosis and management of cancer patients. Peripheral whole blood is a "nucleic acid-rich" and "inflammatory cell-rich" information reservoir and represents systemic processes altered by the presence of cancer cells.We conducted transcriptome profiling of whole blood cells from melanoma patients. To overcome challenges associated with blood-based transcriptome analysis, we used a PAXgene™ tube and NuGEN Ovation™ globin reduction system. The combined use of these systems in microarray resulted in the identification of 78 unique genes differentially expressed in the blood of melanoma patients. Of these, 68 genes were further analyzed by quantitative reverse transcriptase PCR using blood samples from 45 newly diagnosed melanoma patients (stage I to IV) and 50 healthy control individuals. Thirty-nine genes were verified to be differentially expressed in blood samples from melanoma patients. A stepwise logit analysis selected eighteen 2-gene signatures that distinguish melanoma from healthy controls. Of these, a 2-gene signature consisting of PLEK2 and C1QB led to the best result that correctly classified 93.3% melanoma patients and 90% healthy controls. Both genes were upregulated in blood samples of melanoma patients from all stages. Further analysis using blood fractionation showed that CD45(-) and CD45(+) populations were responsible for the altered expression levels of PLEK2 and C1QB, respectively.The current study provides the first analysis of whole blood-based transcriptome biomarkers for malignant melanoma. The expression of PLEK2, the strongest gene to classify melanoma patients, in CD45(-) subsets illustrates the importance of analyzing whole blood cells for biomarker studies. The study suggests that transcriptome profiling of blood cells could be used for both early detection of melanoma and monitoring of patients for residual disease