Innovations In Clinical Neuroscience

ISCTM Supplement 2015

A peer-reviewed, evidence-based journal for clinicians in the field of neuroscience

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[ V O L U M E 1 2 , N U M B E R 3 – 4 , S U P P L E M E N T A , M A R C H – A P R I L 2 0 1 5 ] Innovations in CLINICAL NEUROSCIENCE 37S several factors, some blood markers establish an equilibrium with CSF by readily crossing the blood brain barrier and are therefore more likely to be i nformative. Also, there is some "leakage" between blood and CSF of substances that are not usually considered as permeant, particularly under conditions of inflammation. BDNF is an example of a peripheral marker that has been reported to differ between patient samples and healthy controls and to predict treatment response, despite debate about whether the origins of peripheral BDNF are from CNS or peripheral sources, such as platelets. To address this issue, Pillai et al 7 8 measured peripheral and CSF BDNF concentrations and found a significant correlation coefficient of r=0.51. In general, demonstration of a significant relationship between peripheral and CNS concentrations or activity strengthens a claim for the potential utility of peripheral biomarker candidates. An additional argument for certain peripheral markers, such as lymphocytes or fibroblasts, is that they may mirror cells in the CNS. Several studies have reported strong associations between markers obtained from these peripheral cells and CNS. In one notable example, Mondelli et al 79 found that expression in lymphocytes of BDNF and the inflammatory cytokine, IL-6, accounted for 73 percent of the variance in left hippocampal volume in unmedicated patients with first episode psychosis. Salivary cortisol concentrations further increased the predictive value. While replication will be important, this study also illustrates the approach of sampling factors known to influence brain development and function, in this case inflammation, stress, and growth factors. Consistent with this model, Chan et al 80 recently reviewed 185 publications that reported 273 peripheral biomarkers in schizophrenia plus 7 multi-center studies that identified 137 blood biomarkers. The authors of this review similarly concluded that markers related to inflammation, cortisol and growth factors were most strongly implicated in schizophrenia and were most promising as predictors of treatment response. Additional strategies have recently s hown promise for the identification of potential biomarkers. Employing a proteomics approach, Schwarz et al 81 screened 181 proteins in blood from 250 medication-naïve first episode psychosis subjects compared to healthy controls. They found that a combination of 34 analytes correctly identified 75% of cases: these analytes primarily represented inflammatory, hormonal, metabolic, and neurotrophic factors. Aberg et al 82 examined epigenetic factors by performing a methylome-wide association study in 759 individuals with schizophrenia and in matched healthy controls. They examined 68 million methylation sites per subject and performed an independent replication. Methylation signals that differentiated patients from controls were found in networks associated with neuronal differentiation of DA cells, hypoxia, inflammation and reelin. In summary, traditional approaches to biomarkers have found little clinical application in schizophrenia. Recent advances in PET ligands and fMRI may facilitate early drug development. "Big data" is driving more complex models of illness and identifying networks of potential novel biomarkers. While peripheral biomarkers are of less certain validity in reflecting the CNS due to the blood brain barrier, several approaches have produced promising results. New biomarkers based on inflammation, stress, and neurodevelopmental factors may be of particular value for drug development in prodrome and early stages of the illness. A combination of peripheral markers may therefore support the proper diagnosis of schizophrenia and provide the basis of a more biologically homogeneous patient selection. The outcome of clinical trials would be dramatically de-risked on the basis of a lesser biological variability of the enrolled subjects. CONCLUSION Biomarkers can be utilized for a variety of purposes in different contexts. The understanding of the c onceptual differentiation between these different modes is one important obstacle for their use. An overview is provided in Table 1. 5–8 The main objective of the utilization of biomarkers in the current context is firstly, a means to identify the right patient (i.e., to define differential markers to classify patients into biomarker positive and biomarker negative groups for patient stratification, and finally, selection). These potentially predictive markers may or may not change with treatment (in contrast to hypothetical surrogate markers, which is expected to change with clinical improvement). We saw that predictive markers can be genetic, physiological or biochemical markers as well as markers of a clinically defined subgroup. Accomplishing such a goal will necessitate careful pilot work and then hypothesis testing in definitive trials to demonstrate and replicate differential efficacy. Biomarkers demonstrated to be useful may be permitted into labeling, provided that practical methods are available for identifying relevant patient subgroups. Future biomarkers may permit the sub-grouping of heterogeneous populations into responsive and non-responsive sub- types. The definition of a patient population on the basis of biological criteria would at the same time overcome the diagnostic uncertainty, which many trials may face, as "professional" patients may try to get enrolled. The second objective, pointing to the issue of the right dose, is the question of target engagement. Functional markers for nearly any CNS active compound can be derived from its mechanism of action and independent of any assumptions of disease biology. These can be assessed shortly after the beginning of drug administration and have their value as necessary markers for response and may support the prediction of long term outcome. These markers could in

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