Epigenetic Age Acceleration and Psychoneurological Symptoms in Sickle Cell Disease

点击翻译按钮获取中文摘要

PROJECT SUMMARY Individuals with sickle cell disease (SCD) experience deleterious psychoneurological symptoms, such as pain, sleep disturbances, depressive symptoms, and cognitive impairment. Among these symptoms, there is notable interindividual variability. Few studies have sought to examine why some individuals experience worse psychoneurological symptoms than others. Identifying biological factors, such as epigenetic mechanisms that influence the variability of symptom experiences in SCD, can help inform the development of risk assessment tools and interventions that promote health maintenance, quality of life, and reduce health disparities in this population. Recent evidence has converged to suggest a person's epigenetic age may be associated with psychoneurological symptom experiences in SCD. Epigenetic age is calculated by assessing DNA methylation patterns at numerous CpG loci that account for the pace of cellular aging or declining tissue function. Premature epigenetic age acceleration putatively involves many physiologic processes, including increased inflammation, oxidative stress, and mitochondrial dysfunction. Associations with epigenetic age acceleration and psychoneurological symptom experiences in other chronic disease populations has recently been identified. However, whether epigenetic age acceleration occurs and if it is associated with these symptoms in individuals with SCD remains unknown. The specific aims of this cross-sectional study are to 1) characterize epigenetic aging DNA methylation patterns and determine presence of epigenetic age acceleration and 2) identify associations between epigenetic age acceleration and psychoneurological symptoms (pain, sleep disturbances, depressive symptoms, and cognitive function) in adults with SCD. DNA samples and patient- reported outcome data already collected at Duke University as part of the Sickle Cell Disease Consortium Research Registry (n=92) will be used in this study. DNA methylation data will be generated from the extracted DNA of blood specimens and used to calculate epigenetic age. Because different epigenetic clocks provide different measures and characteristics of epigenetic aging, epigenetic age acceleration will be calculated using three epigenetic clocks (Horvath, Hannum, and Levine). We will also examine whether the calculations from each of the clocks are correlated in the sample. Patient-reported data for each symptom of interest existing in the SCDIC Registry will be used to determine associations with epigenetic age acceleration for each of the epigenetic clocks. This “high risk, high return” study may provide novel insight into epigenetic aging biomarkers associated with symptom development and health outcomes in people with SCD, an underrepresented population. The data generated is essential for designing a rigorous and adequately powered R01 study to understand the interactions of multiple level factors (e.g., epigenetic age acceleration, social determinants such as discrimination and racism) that contribute to symptom burden and health disparities in this population.