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Research Project

Multi-Omics Analysis of Psychoneurological Symptoms Among Cancer Survivors

Principal Investigator
Li, Hongjin
Start Date
End Date
Funding Source
Heilbrunn Nurse Scholar Award


Psychoneurological (PN) symptoms such as pain, fatigue, depression, anxiety, and sleep disturbance are the most distressing symptoms among cancer survivors. These symptoms have a detrimental impact on cancer survivors’ functional status and quality of life. Inter-individual variability of the experience of PN symptoms has been reported in cancer survivors. It is critical to identify individualized biomarkers to better understand the inter-individual variability of PN symptoms. Genetics and metabolomics are promising omics approaches for understanding symptom phenotypes. Recently, our research group identified three genes regulating the hypothalamic-pituitary-adrenal axis associated with PN symptoms among women with breast cancer. We also identified 10 functional genetic polymorphisms to serve as stable common data elements for PN symptoms. In addition, metabolomics provides a more accurate representation of phenotypes and reflects metabolic changes resulting from genetic variation and environmental stimulation. The untargeted metabolomics profiling can provide a holistic understanding of mechanisms underlying PN symptoms. To our knowledge, no previous studies have integrated genomic and metabolomic data to understand PN symptoms among cancer survivors. Consequently, the purpose of the proposed study is to combine genetic and metabolomics data and apply a machine learning technique to better understand inter-individual variability in PN symptoms among cancer survivors. This study will leverage symptom data (n=82) currently being collected among cancer survivors under a K23 study and will include collection of new biospecimen samples. Results from this study will better explain individual differences and mechanisms underlying PN symptoms and will serve as a foundation for future interventions studies to manage sy