Genomic Analyses for Elucidating Novel Targets for Symptoms Management

National Institute Of Nursing Research

Investigators

Linked publications & trials

Abstract

Most symptoms are multifactorial in origin with both genetic and environmental factors contributing to individual variations. Candidate gene studies on the basis of biological hypotheses have been performed to identify relevant genetic variation in complex traits such as pain and neurological symptoms. However, the complicated mesh of contributing factors and the thousands of molecules involved in different symptoms makes it difficult to detect responsible genetic factors for an individuals unique susceptibility to disorders. It is unlikely that common variations in a single gene act dominantly on complex traits; rather, the contribution of each gene seems to be subtle, acting on one of multiple biological pathways, making its signal difficult to detect. The combined impact of the rapid increase in knowledge of diseases and the ability to apply powerful and high capacity technology has raised expectations for more effective and safer medicines for various types of symptoms management. Developing new treatment strategies for symptoms management is also critically dependent on identifying new target molecules and defining phenotypes for specific types of disorders. Therefore, the first step of this project has been to define the characteristics of experimental and clinical phenotypes. We have launched multiple projects with -omics technology such as next generation sequencing, somalogic proteomics, etc, which allow us to perform entire and/or targeted sequencing of nucleotides and proteins in unbiased manner. The role of genetic and epigenetic factors on symptoms in various disorders and/or conditions will continue to be studied along with their behavio-social factors. For example, in neurological disorders such as acute and chronic pain, sleep disorders, mild traumatic brain injury and PTSD, we are using NGS for genotyping, gene and protein expression profiling, and patient reported outcomes to better understand the reciprocal interplay between these factors and the numerous biologic/mechanistic pathways including the inflammatory cascade. Gene expression profiles using unbiased RNA-seq technology from soldiers who suffered from blast injury were presented at multiple meetings. We also presented miRNA analysis from soldiers back from war zone. These results of gene expression profiles based on NGS data were compared to the civilians data and published. We launched a project of RNA-seq with multiple chronic conditions including chronic low back pain, TMD, IBS, fatigue and sleep disturbance to decipher genetic roles in those symptoms and the result was published. Preliminarily, we found 3-5 common genes associated with multiple chronic conditions simultaneously. Based on the data generated from whole genome approaches, we also narrowed and used targeted analysis such as NanoString and validated NGS results of blast injury patients. Two epigenetic studies using DNA methylation chromatin immunoprecipitation followed by whole genome scale sequencing were conducted from civilian and military groups. The results were also presented at multiple meetings and published. Epigenetic changes in military PTSD patients was published while the epigenetic study in sports related concussion patients was submitted for publication and is currently under review. To expand this, we ran whole genome sequencing following bisulfite treatment of genomic DNA to increase the resolution of methylated CpG island identification in PTSD patients alogn with their psychological symptoms and submitted. Because the data size from sequencing after bisulfite conversion is hundreds Gbs per each patient, establishing pipe line for analysis is challenging. We could successfully establish its pipeline and could finish analysis of this DNA methylation-seq data this year. Considering that the protein is the final product from DNA and RNA, protein analysis from those multiple projects has been recently launched. We especially focus on proteins showing trace amount only so that it makes difficult to detect with conventional protein assays such as ELISA. So far, we have successfully detected tau and p-tau protein in plasma, which has not been measured with ELISA. And its result of tau protein in military TBI patients was published. Multiplexing assays are now used for more effective and fast data collection. We published data from this highly sensitive instrument like SIMOA in various neurological disorder patients. We also expanded to Somalogic Scan system which can measure a few thousands of proteins in one time run. We submitted a study based on this Somalogic Scan system. Developing new analyzing methods for the high throughput big data generated by the omics platforms including whole genome sequencing, gene expression signatures, epigenetics and their interactions with other factors such as proteins and environment factors is another goal of these projects. Also, using gene editing technologies, we will try to develop new treatment strategies based on genomics. Recent studies suggest central nervous system communicates with peripheral nervous system via exosomes. Therefore, we started exosome analysis using Nanosight 300 or Spectradyne followed by either exosomal micro RNA analysis or protein analysis. Findings of proteomic data from exosome in kidney transplant patients was published. MicroRNA from exosomes in plasma, serum and urine were also isolated and analyzed using NanoString miRNA panel from multiple disease conditions. Results were published. Also, single cell assays using ddSeq from BioRad were recently acquired and optimized. We have analyzed PBMCs from stroke patients to decipher the role of each blood cell type in the underlying mechanism and its recovery process based on single cell assay. We sequenced 20 samples with 30,000 individual single cell transcriptome profile for preliminary analysis of stroke patients. We submitted its preliminary results and two manuscripts from this study are currently under the review. we also submitted a manuscript regarding transcriptome changes across the course of mild stroke patients along with their MRI findings and it is currently under review too. Also, we developed a validation strategy for single cell transcriptome profile using flow cell cytometry, which confirmed our results based on single cell RNA-seq with FACS data. Flow cytometry is also used to validate results of exosome studies. From these results, along with biological knowledge of multiple pathways in neurological disorders, we will be able to suggest molecular-genetic mechanisms of those diseases at the level of the individual. Finally, we can suggest integrative genomic analysis to develop new drugs and test them based on individual genetic information.