RNA biomarkers for alcohol use disorder

下一代测序和其他组学技术刺激了精确度的发展

Next generation sequencing and other -omics technologies have spurred the development of precision medicine, but this field is still in its infancy for alcohol use disorder (AUD). Transcriptomic studies have established that alcohol use causes widespread changes in brain gene expression. Brain gene expression profiles can identify alcohol-dependent human subjects and mice and can be used to repurpose pharmaceuticals that reduce excessive alcohol consumption in rodents. However, it is not possible to obtain brain samples from living patients, which limits the translational potential of this approach. Routine blood testing has long been a part of medical care. Blood genomic profiles could potentially be used to non-invasively determine whether a patient is at risk for AUD, provide data-driven diagnosis of AUD, stratify the heterogeneous AUD patient population for clinical trials, select optimal therapy, and monitor treatment response and disease progression. As a first step toward these goals, Dr. Ferguson analyzed gene expression patterns in paired blood and brain samples from mice subjected to chronic intermittent ethanol (CIE) exposure, a mouse model of alcohol dependence. Blood gene expression signatures of CIE predicted a pharmaceutical that reduced alcohol drinking in mice, and predictive models built from blood profiles distinguished between CIE and air-exposed mice with high accuracy. These results lead to the hypothesis that blood can serve as a proxy for brain tissue in molecular-based diagnostic or therapeutic tools and advance personalized medicine approaches for AUD. However, it is not known whether there is a biological signature of AUD in blood from a human population. Furthermore, there is a need for biomarkers to predict and monitor treatment success and it is unknown whether blood gene expression profiles might be useful in this regard. The CIE blood signature used in the previous study assayed the transcriptome only at a single time point. Therefore, the dynamics or ongoing transition of important gene regulatory functions were not investigated. These gaps in knowledge will be addressed in proposed Aims by analyzing blood profiles (1) across multiple time points throughout alcohol withdrawal in humans (Aim 1), (2) across multiple time points through the development of CIE-induced alcohol dependence in mice (Aim 2), and (3) before and after treatment in humans and mice (Aim 3). The overarching hypothesis is that genomic profiles from blood will improve the clinical management of AUD including diagnosis, prognosis, and predicting treatment response. These Aims and the accompanying training plan were designed to build on Dr. Ferguson’s previous research experiences and facilitate new scientific training in clinical alcohol research and biostatistical analyses of longitudinal data, time-to-event outcome data, and treatment effect estimation. The proposed Pathway to Independence Award will generate new knowledge about a relatively unstudied area in alcohol research and enable Dr. Ferguson to establish a solid framework for building a successful research program as an academic translational neuroscientist in the alcohol field.