Evidence of associations between cytokine genes and subjective reports of sleep disturbance in oncology patients and their family caregivers

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

Research output: Contribution to journalArticle

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.

Original languageEnglish (US)
Article numbere40560
JournalPLoS One
Volume7
Issue number7
DOIs
StatePublished - Jul 23 2012

Fingerprint

animal technicians
Oncology
sleep
Caregivers
Sleep
cytokines
Genes
Cytokines
genes
trajectories
Trajectories
Karnofsky Performance Status
Radiotherapy
radiotherapy
Polymorphism
Genetic Markers
Brain Neoplasms
Haplotypes
single nucleotide polymorphism
signs and symptoms (animals and humans)

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

Cite this

Evidence of associations between cytokine genes and subjective reports of sleep disturbance in oncology patients and their family caregivers. / Miaskowski, Christine; Cooper, Bruce A.; Dhruva, Anand; Dunn, Laura B.; Langford, Dale J.; Cataldo, Janine K.; Baggott, Christina R.; Merriman, John D.; Dodd, Marylin; Lee, Kathryn; West, Claudia; Paul, Steven M.; Aouizerat, Bradley E.

In: PLoS One, Vol. 7, No. 7, e40560, 23.07.2012.

Research output: Contribution to journalArticle

Miaskowski, C, Cooper, BA, Dhruva, A, Dunn, LB, Langford, DJ, Cataldo, JK, Baggott, CR, Merriman, JD, Dodd, M, Lee, K, West, C, Paul, SM & Aouizerat, BE 2012, 'Evidence of associations between cytokine genes and subjective reports of sleep disturbance in oncology patients and their family caregivers', PLoS One, vol. 7, no. 7, e40560. https://doi.org/10.1371/journal.pone.0040560
Miaskowski, Christine ; Cooper, Bruce A. ; Dhruva, Anand ; Dunn, Laura B. ; Langford, Dale J. ; Cataldo, Janine K. ; Baggott, Christina R. ; Merriman, John D. ; Dodd, Marylin ; Lee, Kathryn ; West, Claudia ; Paul, Steven M. ; Aouizerat, Bradley E. / Evidence of associations between cytokine genes and subjective reports of sleep disturbance in oncology patients and their family caregivers. In: PLoS One. 2012 ; Vol. 7, No. 7.
@article{1bf533acec67417bbf6c05025e5380e5,
title = "Evidence of associations between cytokine genes and subjective reports of sleep disturbance in oncology patients and their family caregivers",
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.",
author = "Christine Miaskowski and Cooper, {Bruce A.} and Anand Dhruva and Dunn, {Laura B.} and Langford, {Dale J.} and Cataldo, {Janine K.} and Baggott, {Christina R.} and Merriman, {John D.} and Marylin Dodd and Kathryn Lee and Claudia West and Paul, {Steven M.} and Aouizerat, {Bradley E.}",
year = "2012",
month = "7",
day = "23",
doi = "10.1371/journal.pone.0040560",
language = "English (US)",
volume = "7",
journal = "PLoS One",
issn = "1932-6203",
publisher = "Public Library of Science",
number = "7",

}

TY - JOUR

T1 - Evidence of associations between cytokine genes and subjective reports of sleep disturbance in oncology patients and their family caregivers

AU - Miaskowski, Christine

AU - Cooper, Bruce A.

AU - Dhruva, Anand

AU - Dunn, Laura B.

AU - Langford, Dale J.

AU - Cataldo, Janine K.

AU - Baggott, Christina R.

AU - Merriman, John D.

AU - Dodd, Marylin

AU - Lee, Kathryn

AU - West, Claudia

AU - Paul, Steven M.

AU - Aouizerat, Bradley E.

PY - 2012/7/23

Y1 - 2012/7/23

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84864241045&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84864241045&partnerID=8YFLogxK

U2 - 10.1371/journal.pone.0040560

DO - 10.1371/journal.pone.0040560

M3 - Article

VL - 7

JO - PLoS One

JF - PLoS One

SN - 1932-6203

IS - 7

M1 - e40560

ER -