Article

Evidence of Associations between Cytokine Genes and Subjective Reports of Sleep Disturbance in Oncology Patients and Their Family Caregivers

Department of Physiological Nursing, University of California San Francisco, San Francisco, California, United States of America.
PLoS ONE (Impact Factor: 3.23). 07/2012; 7(7):e40560. DOI: 10.1371/journal.pone.0040560
Source: PubMed

ABSTRACT The purposes of this study were to identify distinct latent classes of individuals based on subjective reports of sleep disturbance; to examine differences in demographic, clinical, and symptom characteristics between the latent classes; and to evaluate for variations in pro- and anti-inflammatory cytokine genes between the latent classes. Among 167 oncology outpatients with breast, prostate, lung, or brain cancer and 85 of their FCs, growth mixture modeling (GMM) was used to identify latent classes of individuals based on General Sleep Disturbance Scale (GSDS) obtained prior to, during, and for four months following completion of radiation therapy. Single nucleotide polymorphisms (SNPs) and haplotypes in candidate cytokine genes were interrogated for differences between the two latent classes. Multiple logistic regression was used to assess the effect of phenotypic and genotypic characteristics on GSDS group membership. Two latent classes were identified: lower sleep disturbance (88.5%) and higher sleep disturbance (11.5%). Participants who were younger and had a lower Karnofsky Performance status score were more likely to be in the higher sleep disturbance class. Variation in two cytokine genes (i.e., IL6, NFKB) predicted latent class membership. Evidence was found for latent classes with distinct sleep disturbance trajectories. Unique genetic markers in cytokine genes may partially explain the interindividual heterogeneity characterizing these trajectories.

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    • " with larger sample sizes are needed to confirm these findings and identify additional latent classes and / or significant phenotypic predictors . Differences in demographic ( e . g . , gender ) and clinical ( e . g . , homogenous versus heterogeneous cancer diagnoses ) characteristics between partici - pants in this study and our previous study ( Miaskowski et al . , 2012b"
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    ABSTRACT: 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. 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. 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. 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.
    European journal of oncology nursing: the official journal of European Oncology Nursing Society 09/2013; 18(1). DOI:10.1016/j.ejon.2013.08.004 · 1.79 Impact Factor
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    • "The AFI produced scores ranging from 55–82. Patients who score 50 to 75 function moderately well and patients who score >75 function well [29]. "
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    BMC Nursing 11/2012; 11(1):27. DOI:10.1186/1472-6955-11-27
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