Genomic Analyses for Elucidating Novel Targets for Symptoms Management

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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. Contributing factors such as gender, ethnicity and psychological factors predominate over the role of genetic factors in pain and analgesic responses when evaluating groups of patients (Kim et al. 2004a; Kim et al. 2004b). But genetic variability may be important at the level of the individual (Dionne et al. 2005). We published a whole genome scan study related to clinical symptoms using 500,000 SNPs assay in the clinical symptoms(Kim et al. 2009, Pharmacogenomics). We have expanded the number of testing SNPs up to 1 million from human genome and are genotyping hundreds of patients with fibromyalgia, acute coronary syndrome and subarrachnoid hemorrhage. Results from those studies were reported at the annual meetings of American Pain Society, American Society of Human Genetics and International Stroke Conference. Detailed information and functional genomic studies of the candidate regions from those projects may provide knowledge for the genetic role in responses to tissue injury, pain and analgesia and other neurological symptoms on an individual patient basis. Also the result of genetic association in the evidence of cerebral vasospasm based on transcranial doppler signals in subarrachnoid hemorrhage patients was publishced in 2012 (Kim et al. 2012, Int J of Stroke). Same technology has been applied to investigate the association for the PTSD and phantom limb pain from service members returned from war zone. Recently, we launched projects with next generation sequencing technology, which allows us perform entire genome sequencing for individuals with unique phenotypes such as capsaicin non-sensitive patients, and epigenetic changes following long term environmental changes such as soldiers exposed to combat, and traumatic brain injury resulted to the post traumatic stress disorder. The role of genetic and epigenetic factors on clinical pain will continue to be studied in neurological disorders such as acute pain and PTSD using genotyping, gene and protein expression, and patient reported outcomes to better understand the reciprocal interplay between these factors and the inflammatory cascade. These data will be analyzed with whole genome sequencing, microarray, ELISA, SNP genotyping, and real time PCR. Gene expression profiles from the soldiers back from war zone were presented at the multiple meetings (CNRM and ASN meeting). Epigeetic changes in the cancer fatigue patients will also be presented at the ASHG meeting this year. Using the next generation sequencing technology, we also launched microbiome projects to characterize population of microorganisms in human body. Developing new analyzing methods for the high throughput data generated by the next generation sequencers is another goal of these projects. 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.