Association between pro- and anti-inflammatory cytokine genes and a symptom cluster of pain, fatigue, sleep disturbance, and depression

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• 作者：Julie Illi^a ; Christine Miaskowski^a ; ^{chris.miaskowski@nursing.ucsf.edu} ; Bruce Cooper^a ; Jon D. Levine^b ; ^c ; Laura Dunn^b ; Claudia West^a ; Marylin Dodd^a ; Anand Dhruva^b ; Steven M. Paul^a ; Christina Baggott^a ; Janine Cataldo^a ; Dale Langford^a ; Brian Schmidt^e ; Bradley E. Aouizerat^a ; ^d
• 关键词：AIMs ; ancestry informative markers ; BIC ; Bayesian Information Criterion ; BLRT ; bootstrapped likelihood ratio test ; CES-D ; Center for Epidemiological Studies- Depression Scale ; CI ; confidence interval ; DNA ; deoxyribonucleic acid ; EM ; expectation&ndash ; maxi
• 刊名：Cytokine
• 出版年：2012
• 期刊代码：97_10434666
• 类别：imm
• 出版时间：June, 2012
• 卷：58
• 期：3
• 页码：437-447
• 文件大小：264 K

摘要

Because multiple symptoms associated with 鈥渟ickness behavior鈥?have a negative impact on functional status and quality of life, increased information on the mechanisms that underlie inter-individual variability in this symptom experience is needed. The purposes of this study were to determine: if distinct classes of individuals could be identified based on their experience with pain, fatigue, sleep disturbance, and depression; if these classes differed on demographic and clinical characteristics; and if variations in pro- and anti- inflammatory cytokine genes were associated with latent class membership.

Self-report measures of pain, fatigue, sleep disturbance, and depression were completed by 168 oncology outpatients and 85 family caregivers (FCs). Using latent class profile analysis (LCPA), three relatively distinct classes were identified: those who reported low depression and low pain (83%), those who reported high depression and low pain (4.7%), and those who reported high levels of all four symptoms (12.3%). The minor allele of IL4 rs2243248 was associated with membership in the 鈥淎ll high鈥?class along with younger age, being White, being a patient (versus a FC), having a lower functional status score, and having a higher number of comorbid conditions.

Findings suggest that LPCA can be used to differentiate distinct phenotypes based on a symptom cluster associated with sickness behavior. Identification of distinct phenotypes provides new evidence for the role of IL4 in the modulation of a sickness behavior symptom cluster in oncology patients and their FCs.