Peripheral Blood As Tool To Determine Gene Expression Patterns In Patients With Psychiatric, Neurological And Other Common Disorders: A Systematic Review And Meta-Analysis Protocol

IntroductionCommon diseases are influenced by a variety of factors that can enhance one persons susceptibility to developing a specific condition. Complex traits have been investigated in several biological levels. One that reflects the high interconnectivity and interaction of genes, proteins and transcription factors is the transcriptome. In this study, we disclose the protocol for a systematic review and meta-analysis aiming at summarizing the available evidence regarding transcriptomic gene expression levels of peripheral blood samples comparing subjects with psychiatric, neurological and other common disorders to healthy controls. Methods and analysisThe investigation of the transcriptomic levels in the peripheral blood enables the unique opportunity to unravel the etiology of common diseases in patients ex-vivo. However, the experimental results should be minimally consistent across studies for them to be considered as the best approximation of the true effect. In order to test this, we will systematically identify all transcriptome studies that compared subjects with common disorders to their respective control samples. We will apply meta-analyses to assess the overall differentially expressed genes throughout the studies of each condition. Ethics and disseminationThe data that will be used to conduct this study are available online and have already been published following their own ethical laws. Therefore this study requires no further ethical approval. The results of this study will be published in leading peer-reviewed journals of the area and also presented at relevant national and international conferences. Strengths and limitations of this study We present a new and systematically centered method to assess the overall effect of transcriptomic levels in the blood of subjects with common conditions. Meta-analyses are a robust statistical method to assess effect sizes across studies. The analysis is limited by the availability of studies, as well as their quality and comprehensiveness. Subgroup and meta-regression analyses will be also limited by the amount and quality of sample characterization variables made available by original studies.