title: Cytokine gene variation is associated with depressive symptom trajectories in oncology patients and family caregivers.
abstract: OBJECTIVE
  Depressive symptoms are common in cancer patients and their family caregivers (FCs). While these symptoms are characterized by substantial interindividual variability, the factors that predict this variability remain largely unknown. This study sought to confirm latent classes of oncology patients and FCs with distinct depressive symptom trajectories and to examine differences in phenotypic and genotypic characteristics among these classes.
  
  
  METHODS
  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 Center for Epidemiological Studies-Depression (CES-D) scores obtained prior to, during, and for four months following completion of radiation therapy. One hundred four single nucleotide polymorphisms (SNPs) and haplotypes in 15 candidate cytokine genes were interrogated for differences between the two largest latent classes. Multivariate logistic regression analyses assessed effects of phenotypic and genotypic characteristics on class membership.
  
  
  RESULTS
  Four latent classes were confirmed: Resilient (56.3%), Subsyndromal (32.5%), Delayed (5.2%), and Peak (6.0%). Participants who were younger, female, non-white, and who reported higher baseline trait and state anxiety were more likely to be in the Subsyndromal, Delayed, or Peak groups. Variation in three cytokine genes (i.e., interleukin 1 receptor 2 [IL1R2], IL10, tumor necrosis factor alpha [TNFA]), age, and performance status predicted membership in the Resilient versus Subsyndromal classes.
  
  
  CONCLUSIONS
  Findings confirm the four latent classes of depressive symptom trajectories previously identified in a sample of breast cancer patients. Variations in cytokine genes may influence variability in depressive symptom trajectories.
authors.affiliation: School of Medicine, University of California, San Francisco, CA, USA. laura.dunn@ucsf.edu
authors.forename: Laura B
authors.initials: LB
authors.lastname: Dunn
authors.forename: Bradley E
authors.initials: BE
authors.lastname: Aouizerat
authors.forename: Dale J
authors.initials: DJ
authors.lastname: Langford
authors.forename: Bruce A
authors.initials: BA
authors.lastname: Cooper
authors.forename: Anand
authors.initials: A
authors.lastname: Dhruva
authors.forename: Janine K
authors.initials: JK
authors.lastname: Cataldo
authors.forename: Christina R
authors.initials: CR
authors.lastname: Baggott
authors.forename: John D
authors.initials: JD
authors.lastname: Merriman
authors.forename: Marylin
authors.initials: M
authors.lastname: Dodd
authors.forename: Claudia
authors.initials: C
authors.lastname: West
authors.forename: Steven M
authors.initials: SM
authors.lastname: Paul
authors.forename: Christine
authors.initials: C
authors.lastname: Miaskowski
mesh_terms: D000328:Adult; D017677:Age Distribution; D000368:Aged; D002140:California; D017028:Caregivers / Q000523:psychology* / Q000706:statistics & numerical data; D015331:Cohort Studies; D015897:Comorbidity; D016207:Cytokines / Q000235:genetics*; D003863:Depression / Q000453:epidemiology* / Q000235:genetics*; D005260:Female; D005500:Follow-Up Studies; D020022:Genetic Predisposition to Disease / Q000453:epidemiology; D014644:Genetic Variation; D005838:Genotype; D006801:Humans; D015994:Incidence; D016015:Logistic Models; D008297:Male; D008495:Medical Oncology; D008875:Middle Aged; D015999:Multivariate Analysis; D009369:Neoplasms / Q000453:epidemiology* / Q000523:psychology*; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D012720:Severity of Illness Index; D017678:Sex Distribution
chemical_list: D016207:Cytokines