Ideally, samples should contain less than ten red blood cells per microliter of CSF

Ideally, samples should contain less than ten red blood cells per microliter of CSF. Metabolomics Overview of metabolomic techniques As the development of targeted assays is Nilutamide well described in the literature, we will focus on summarizing the methodology involved in fingerprinting metabolomics. and or model of genetic susceptibility is simultaneously exposed to an environmental toxicant, further supporting a multifaceted disease etiology [40]. Given the complexity that surrounds both the etiology of the disease, as well as the pathological cascades that follow, a more comprehensive investigation of PD and the identification of specific disease networks and molecular pathways involved will facilitate our understanding of the disease process and enhance our ability to diagnose and treat this debilitating condition. A recent effort has focused on the use of -omics, particularly transcriptomics, proteomics and metabolomics, in order to elucidate many of the pathogenic aspects of PD. Notably, Nilutamide when we discuss these techniques we are referring to the use of transcriptomics to identify genes and evaluate changes in gene expression, while proteomics is focused on recognizing and measuring respective changes in proteins. Finally, metabolomics is concerned with the identification and quantification of metabolites to provide a signature of the metabolic state at that point in time. In general, these techniques can be applied to various biological media, including tissue, cerebrospinal fluid (CSF), blood and blood constituents and urine, as well as others. These platforms provide a means to generate and analyze a significant amount of data with the intent of facilitating studies to reveal the molecular events that underlie neurodegeneration in PD. Moreover, the integration of gene, protein and metabolic targets would generate a cohesive picture of shared pathways and variations between the healthy and disease state. Furthermore, the application of these approaches can be extensively utilized in the discovery of biomarkers of PD. Biomarkers are used as indicators of normal biological processes, as well as pathologic processes, and can provide a window into the disease mechanism with the hope of developing specific therapeutic targets of the disease. In addition, from a clinical point of view, the development of biomarkers that allow Ldb2 for the delineation of premotor stages of PD from more advanced pathologic states would greatly enhance the diagnostic power of the clinician and widen the currently narrow Nilutamide therapeutic window available for treatment. In this regard, transcriptomics, proteomics and metabolomics could be used separately or in conjunction to discover biomarkers. Thus, biomarkers are imperative to our understanding of PD pathogenesis and progression. The intent of this article is to appraise and summarize the current PD research in the context of transcriptomic, proteomic and metabolomic platforms and findings. Given the exponential growth in the utilization of these techniques in PD, as well as other neurodegenerative disorders, we will focus our article on research reports in which human samples (brain tissue, CSF, blood and plasma) have been used. However, a future appraisal of the application of -omics to cellular, as well as animal, models of PD and the translation of these results to human studies would be extremely beneficial to the field. We will first provide a general overview of each -omic technique followed by an examination of PD-related data generated by each platform. Potential caveats and shortcomings of each technique will also be discussed. Finally, we will identify overlapping targets discovered by transcriptomics, proteomics and metabolomics before discussing future directions associated with the use of -omics in PD research. Transcriptomics Overview of transcriptomics techniques Microarray analysis, also known as gene expression profiling, measures the mRNA levels of all known human genes coding for proteins in a given sample simultaneously. A typical microarray is a glass slide with thousands of spots of oligonucleotide (or cDNA) probes attached to it. Each spot contains thousands of identical copies of one oligonucleotide corresponding to a specific mRNA target. The goal of a typical microarray experiment is to compare gene expression profiles of two or more samples (for overview see Figure 1). The first step of a microarray experiment is the isolation of high-quality RNA. The sample collection procedure and RNA isolation method have to take into account that RNA is labile and subject to rapid degradation. Stringent quality control is critical to ensure high-quality RNA. The second step generates either fluorescently labeled cDNAs or cRNAs from the RNA samples of interest. The third step involves hybridization of the fluorescently labeled sample to the microarray. Microarray platforms can be divided into one or two color platforms. The former uses a single fluorescent dye (one color) and only one sample is.