Associations between cytokine gene variations and self-reported sleep disturbance in women following breast cancer surgery

• Published in: European journal of oncology nursing : the official journal of European Oncology Nursing Society Vol. 18; no. 1; pp. 85 - 93
• Main Authors: Alfaro, Emely, Dhruva, Anand, Langford, Dale J, Koetters, Theresa, Merriman, John D, West, Claudia, Dunn, Laura B, Paul, Steven M, Cooper, Bruce, Cataldo, Janine, Hamolsky, Deborah, Elboim, Charles, Kober, Kord, Aouizerat, Bradley E, Miaskowski, Christine
• Format: Journal Article
• Language: English
• Published: Scotland Elsevier Ltd 01.02.2014
• Subjects: Adult; Age Distribution; Aged; Breast cancer; Breast Neoplasms - pathology; Breast Neoplasms - surgery; Comorbidity; Cytokine genes; Cytokines - genetics; Female; Genes; Genetic Variation; Growth mixture modeling; Hematology, Oncology and Palliative Medicine; Humans; Incidence; Insomnia; Interleukin-6 - genetics; Logistic Models; Longitudinal Studies; Membership; Middle Aged; Multivariate Analysis; NF-kappa B p52 Subunit - genetics; Phenotype; Phenotypes; Polymorphism, Single Nucleotide; Preoperative Care - methods; Risk Assessment; Self Report; Selfreport; Sleep disturbance; Sleep problems; Sleep Wake Disorders - epidemiology; Sleep Wake Disorders - genetics; Surgery; Surveys and Questionnaires; Symptom trajectories; Women; United States > US; Sleep disturbance; Symptom trajectories; Breast cancer; Growth mixture modeling; Insomnia; Cytokine genes
• ISSN: 1462-3889; 1532-2122
• DOI: 10.1016/j.ejon.2013.08.004

Abstract Purpose of the research To attempt to replicate the associations found in our previous study of patients and family caregivers between interleukin 6 (IL6) and nuclear factor kappa beta 2 (NFKB2) and sleep disturbance and to identify additional genetic associations in a larger sample of patients with breast cancer. Methods and sample Patients with breast cancer ( n  = 398) were recruited prior to surgery and followed for six months. Patients completed a self-report measure of sleep disturbance and provided a blood sample for genomic analyses. Growth mixture modeling was used to identify distinct latent classes of patients with higher and lower levels of sleep disturbance. Key results Patients who were younger and who had higher comorbidity and lower functional status were more likely to be in the high sustained sleep disturbance class. Variations in three cytokine genes (i.e., IL1 receptor 2 (IL1R2), IL13, NFKB2) predicted latent class membership. Conclusions Polymorphisms in cytokine genes may partially explain inter-individual variability in sleep disturbance. Determination of high risk phenotypes and associated molecular markers may allow for earlier identification of patients at higher risk for developing sleep disturbance and lead to the development of more targeted clinical interventions.