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

Overview of attention for article published in PLOS ONE, July 2012
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Title
Evidence of Associations between Cytokine Genes and Subjective Reports of Sleep Disturbance in Oncology Patients and Their Family Caregivers
Published in
PLOS ONE, July 2012
DOI 10.1371/journal.pone.0040560
Pubmed ID
Authors

Christine Miaskowski, Bruce A. Cooper, Anand Dhruva, Laura B. Dunn, Dale J. Langford, Janine K. Cataldo, Christina R. Baggott, John D. Merriman, Marylin Dodd, Kathryn Lee, Claudia West, Steven M. Paul, Bradley E. Aouizerat

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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The data shown below were compiled from readership statistics for 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 4%
United Kingdom 1 1%
Unknown 63 94%

Demographic breakdown

Readers by professional status Count As %
Unspecified 10 15%
Student > Master 7 10%
Student > Ph. D. Student 7 10%
Student > Bachelor 6 9%
Professor > Associate Professor 6 9%
Other 15 22%
Unknown 16 24%
Readers by discipline Count As %
Medicine and Dentistry 12 18%
Unspecified 10 15%
Nursing and Health Professions 9 13%
Agricultural and Biological Sciences 3 4%
Psychology 3 4%
Other 9 13%
Unknown 21 31%