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. However, the complicated mesh of contributing factors and the thousands of molecules involved in different symptoms makes it difficult to detect responsible genetic variations 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 next generation sequencing (NGS) technology, which allows us to perform entire and/or targeted genome sequencing in unbiased manner. The role of genetic and epigenetic factors on symptoms in various disorders and/or conditions will continue to be studied. For example, in neurological disorders such as acute and chronic pain, mild traumatic brain injury and PTSD, we are using NGS for genotyping, gene and protein expression, 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 also published. We launched a project of RNA-seq with multiple chronic conditions including chronic low back pain, TMD, IBS and fatigue to decipher genetic roles in those symptoms and currently under analyses. 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 plan to run whole genome sequencing following bisulfite treatment of genomic DNA to increase the resolution of methylated CpG island identification. Whole genome sequencing of special sensory disorder patient and control sibling were sequenced and submitted for publication. Using the targeted next generation sequencing technology, we also have finished a microbiome project to characterize population of microorganisms in human from different disease status. Using a next generation semiconductor sequencer, microbiome was analyzed with extensive sequencing of 16s rRNA region for oral microbiome from the aplastic anemia patients in 2 different ways, sequencing short but multiple sections in 16s rRNA region and full length of 16s rRNA sequencing. The data was presented at the IADR meeting and published. Following microbiome data of aplastic anemia patient group was analyzed with their full dataset and submitted for publication. Mainly the project found that the microbiome composition is altered in specific disease conditions. 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. Developing new analyzing methods for the high throughput big data generated by the next generation sequencers 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 followed by either micro RNA analysis or protein analysis. Findings of proteomic data from exosome in kidney transplant patients was submitted for publication. MicroRNA from exosomes in plasma, serum and urine were also isolated for further analyses including NanoString miRNA panel from multiple disease conditions. Also, single cell assays using 2 different platforms, such as C1 from Fluidigm and 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 keep collecting samples from stroke patients to expand our current findings. Also, we plan to develop validation strategy for single cell transcriptome profile using flow cell cytometry. 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.
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