Faculty Bibliography

INTRODUCTION: The aims of this study were to compare microRNA (miR) expression between individuals with and without insulin resistance and to determine whether miRs predict response to thiazolidinedione treatment. MATERIALS AND METHODS: In a sample of 93 healthy adults, insulin resistance was defined as steady state plasma glucose (SSPG)>/=180mg/dL and insulin sensitive as <120mg/dL. Response to thiazolidinedione therapy was defined as >/=10% decrease in SSPG. We selected a panel of microRNAs based on prior evidence for a role in insulin or glucose metabolism. Fold change and Wilcoxon rank sum tests were calculated for the 25 miRs measured. RESULTS: At baseline, 81% (n=75) of participants were insulin resistant. Five miRs were differentially expressed between the insulin resistant and sensitive groups: miR-193b (1.45 fold change (FC)), miR-22-3p (1.15 FC), miR-320a (1.36 FC), miR-375 (0.59 FC), and miR-486 (1.21 FC) (all p<0.05). In the subset who were insulin resistant at baseline and received thiazolidinediones (n=47), 77% (n=36) showed improved insulin sensitivity. Six miRs were differentially expressed between responders compared to non-responders: miR-20b-5p (1.20 FC), miR-21-5p, (0.92 FC), miR-214-3p (1.13 FC), miR-22-3p (1.14 FC), miR-320a (0.98 FC), and miR-486-5p (1.25 FC) (all p<0.05). DISCUSSION: This study is the first to report miRs associated with response to a pharmacologic intervention for insulin resistance. MiR-320a and miR-486-5p identified responders to thiazolidinedione therapy among the insulin resistant group.

CONTEXT: Fatigue is the most common symptom in oncology patients during chemotherapy (CTX). Little is known about the predictors of interindividual variability in initial levels and trajectories of morning fatigue severity in these patients. OBJECTIVES: An evaluation was done to determine which demographic, clinical, and symptom characteristics were associated with initial levels as well as the trajectories of morning fatigue and to compare findings with our companion paper on evening fatigue. METHODS: A sample of outpatients with breast, gastrointestinal, gynecological, and lung cancer (N=586) completed demographic and symptom questionnaires a total of six times over two cycles of CTX. Fatigue severity was evaluated using the Lee Fatigue Scale. Hierarchical linear modeling (HLM) was used to answer the study objectives. RESULTS: A large amount of interindividual variability was found in the morning fatigue trajectories. A piecewise model fit the data best. Patients with higher body mass index (BMI), who did not exercise regularly, with a lower functional status, and who had higher levels of state anxiety, sleep disturbance and depressive symptoms, reported higher levels of morning fatigue at enrollment. Variations in the trajectories of morning fatigue were predicted by the patients' ethnicity and younger age. CONCLUSION: The modifiable risk factors that were associated with only morning fatigue were BMI, exercise, and state anxiety. Modifiable risk factors that were associated with both morning and evening fatigue included functional status, depressive symptoms, and sleep disturbance. Using this information, clinicians can identify patients at higher risk for more severe morning fatigue and evening fatigue, provide individualized patient education, and tailor interventions to address the modifiable risk factors.

CONTEXT: Fatigue is a distressing, persistent sense of physical tiredness that is not proportional to a person's recent activity. Fatigue impacts patients' treatment decisions and can limit their self-care activities. While significant interindividual variability in fatigue severity has been noted, little is known about predictors of interindividual variability in initial levels and trajectories of evening fatigue severity in oncology patients receiving chemotherapy (CTX). OBJECTIVES: To determine whether demographic, clinical, and symptom characteristics were associated with initial levels as well as the trajectories of evening fatigue. METHODS: A sample of outpatients with breast, gastrointestinal, gynecological, and lung cancer (N=586) completed demographic and symptom questionnaires a total of six times over two cycles of CTX. Fatigue severity was evaluated using the Lee Fatigue Scale. Hierarchical linear modeling (HLM) was used to answer the study objectives. RESULTS: A large amount of interindividual variability was found in the evening fatigue trajectories. A piecewise model fit the data best. Patients who were White, diagnosed with breast, gynecological, or lung cancer, and who had more years of education, child care responsibilities, lower functional status, and higher levels of sleep disturbance and depression reported higher levels of evening fatigue at enrollment. CONCLUSION: This study identified both non-modifiable (e.g., ethnicity) and modifiable (e.g., child care responsibilities, depressive symptoms, sleep disturbance) risk factors for more severe evening fatigue. Using this information, clinicians can identify patients at higher risk for more severe evening fatigue, provide individualized patient education, and tailor interventions to address the modifiable risk factors.

CONTEXT: Cancer patients experience a broad range of physical and psychological symptoms as a result of their disease and its treatment. On average, these patients report 10 unrelieved and co-occurring symptoms. OBJECTIVES: The aims were to determine if subgroups of oncology outpatients receiving active treatment (n = 582) could be identified based on their distinct experience with 13 commonly occurring symptoms; to determine whether these subgroups differed on select demographic and clinical characteristics; and to determine if these subgroups differed on quality of life (QOL) outcomes. METHODS: Demographic, clinical, and symptom data from one Australian and two U.S. studies were combined. Latent class analysis was used to identify patient subgroups with distinct symptom experiences based on self-report data on symptom occurrence using the Memorial Symptom Assessment Scale. RESULTS: Four distinct latent classes were identified (i.e., all low [28.0%], moderate physical and lower psych [26.3%], moderate physical and higher psych [25.4%], and all high [20.3%]). Age, gender, education, cancer diagnosis, and presence of metastatic disease differentiated among the latent classes. Patients in the all high class had the worst QOL scores. CONCLUSION: Findings from this study confirm the large amount of interindividual variability in the symptom experience of oncology patients. The identification of demographic and clinical characteristics that place patients at risk for a higher symptom burden can be used to guide more aggressive and individualized symptom management interventions.

Sleep disturbance has been associated with inflammation and cytokine activity, and we previously described genetic associations between cytokine polymorphisms and sleep maintenance and duration among adults with HIV/AIDS. Although sleep onset insomnia (SOI) is also a commonly reported sleep problem, associations between cytokine biomarkers and SOI have not been adequately studied. The purpose of this study was to describe SOI in relation to cytokine plasma concentrations and gene polymorphisms in a convenience sample of 307 adults (212 men, 72 women, and 23 transgender) living with HIV/AIDS. Based on the Pittsburgh Sleep Quality Index item that asks the time it usually took to fall asleep in the past month, participants were categorized as either >30min to fall asleep (n=70, 23%) or 30min or less to fall asleep (n=237). Plasma cytokines were analyzed, and genotyping was conducted for 15 candidate genes involved in cytokine signaling: interferon-gamma (IFNG), IFNG receptor 1 (IFNGR1), interleukins (IL1R2, IL2, IL4, IL6, IL8, IL10, IL13, IL17A), nuclear factor of kappa light polypeptide gene enhancer in B cells (NFKB1 and NFKB2), and tumor necrosis factor alpha (TNFA). Demographic and clinical variables were evaluated as potential covariates. After adjusting for genomic estimates of ancestry, self-reported race/ethnicity and viral load, SOI was associated with higher IL-13 plasma levels and with six single nucleotide polymorphisms (SNPs): IL1B rs1143642 and rs1143623, IL6 rs4719714, IL13 rs1295686, NFKB1 rs4648110, and TNFA rs2857602. In addition, the IL1B rs1143642 polymorphism was associated with plasma levels of IL-1beta in adjusted analyses. This study strengthens the evidence for an association between inflammation and sleep disturbance, particularly self-report of habitual SOI. In this chronic illness population, the cytokine polymorphisms associated with SOI provide direction for future personalized medicine intervention research.

BACKGROUND: The early sequence of events leading to the development of the acute respiratory distress syndrome (ARDS) in patients with sepsis remains inadequately understood. The purpose of this study was to identify changes in gene expression early in the course of illness, when mechanisms of injury may provide the most relevant treatment and prognostic targets. METHODS: We collected whole blood RNA in critically ill patients admitted from the Emergency Department to the intensive care unit within 24 hours of admission at a tertiary care center. Whole genome expression was compared in patients with sepsis and ARDS to patients with sepsis alone. We selected genes with > 1 log2 fold change and false discovery rate <0.25, determined their significance in the literature and performed pathway analysis. RESULTS: Several genes were upregulated in 29 patients with sepsis with ARDS compared to 28 patients with sepsis alone. The most differentially expressed genes included key mediators of the initial neutrophil response to infection: olfactomedin 4 (OLFM4), lipocalin 2 (LCN2), CD24, and bactericidal/permeability-increasing protein (BPI). These gene expression differences withstood adjustment for age, sex, study batch, white blood cell count and presence of pneumonia or aspiration. Pathway analysis demonstrated over-representation of genes involved in known respiratory and infection pathways. CONCLUSIONS: These data indicate that several neutrophil-related pathways may be involved in the early pathogenesis of sepsis-related ARDS. In addition, identifiable gene expression differences occurring early in the course of sepsis-related ARDS may further elucidate understanding of the neutrophil-related mechanisms in progression to ARDS.

CONTEXT.: Approximately 30% of women report pain in the affected breast prior to breast cancer surgery. OBJECTIVES: The purpose of this secondary analysis of our prospective study was to determine how women who experienced both preoperative and persistent postsurgical breast pain (n=107) differed from women who did not report preoperative breast pain and did (n=158) or did not (n=122) experience persistent postsurgical breast pain. METHODS: Differences in demographic and clinical characteristics were evaluated. Linear mixed effects (LME) modeling was used to evaluate for group differences in symptom severity, function, sensation, and quality of life (QOL) over time. RESULTS: Between-group differences in demographic and clinical characteristics as well as trajectories of shoulder function and QOL were identified. Women with both preoperative and persistent postsurgical breast pain were younger; were more likely to report swelling, strange sensations, hardness, and numbness in the affected breast prior to surgery; and were more likely to have reconstruction at the time of surgery. Women with both preoperative and persistent postsurgical breast pain had more biopsies in the prior year, more lymph nodes removed, and reported more severe acute postsurgical pain than women without preoperative breast pain. LME modeling revealed significant group effects for the majority of outcomes evaluated. Over the six months of the study, women with both preoperative and persistent postsurgical pain had persistently poorer shoulder flexion and physical well-being than women without preoperative breast pain. CONCLUSION: Investigations of the etiology and molecular mechanisms of preoperative breast pain, as well as interventions for this high risk group, are needed.

CONTEXT: Older oncology patients have unique needs associated with the many physical, psychological, and social changes associated with the aging process. The mechanisms underpinning and the impact of these changes are not well understood. Identification of clusters of symptoms is one approach that has been used to elicit hypotheses about the biological and/or psychological basis for variations in symptom experiences. OBJECTIVES: The purposes of this study were to identify and compare symptom clusters in younger (<60 years) and older (>/=60 years) patients undergoing cancer treatment. METHODS: Symptom data from one Australian study and two U.S. studies were combined to conduct this analysis. A total of 593 patients receiving active treatment were dichotomized into younger (<60 years) and older (>/=60 years) groups. Separate exploratory factor analyses (EFAs) were undertaken within each group to identify symptom clusters from occurrence ratings of the 32 symptoms assessed by the Memorial Symptom Assessment Scale. RESULTS: In both groups, a seven-factor solution was selected. Four partially concordant symptom clusters emerged in both groups (i.e., mood/cognitive, malaise, body image, and genitourinary). In the older patients, the three unique clusters reflected physiological changes associated with aging, whereas in the younger group the three unique clusters reflected treatment-related effects. CONCLUSION: The symptom clusters identified in older patients typically included a larger and more diverse range of physical and psychological symptoms. Differences also may be reflective of variations in treatment approaches between age groups. Findings highlight the need for better understanding of variation in treatment and symptom burden between younger and older adults with cancer.

PURPOSE OF THE RESEARCH: Evaluate for associations between variations in genes involved in catecholaminergic, gamma-aminobutyric acid (GABA)-ergic, and serotonergic mechanisms of neurotransmission and attentional function latent classes. PATIENTS AND METHODS: This descriptive, longitudinal study was conducted at two radiation therapy departments. The sample included three latent classes of individuals with distinct trajectories of self-reported attentional function during radiation therapy, who were previously identified using growth mixture modeling among 167 oncology patients and 85 of their family caregivers. Multivariable models were used to evaluate for genotypic associations of neurotransmission genes with attentional function latent class membership, after controlling for covariates. RESULTS: Variations in catecholaminergic (i.e., ADRA1D rs4815675, SLC6A3 rs37022), GABAergic (i.e., SLC6A1 rs2697138), and serotonergic (i.e., HTR2A rs2296972, rs9534496) neurotransmission genes were significant predictors of latent class membership in multivariable models. CONCLUSIONS: Findings suggest that variations in genes that encode for three distinct but related neurotransmission systems are involved in alterations in attentional function. Knowledge of both phenotypic and genetic markers associated with alterations in attentional function can be used by clinicians to identify patients and family caregivers who are at higher risk for this symptom. Increased understanding of the genetic markers associated with alterations in attentional function may provide insights into the underlying mechanisms for this significant clinical problem.

Pain, fatigue, sleep disturbance, and depression are common and frequently co-occurring symptoms in oncology patients. This symptom cluster is often attributed to the release of proinflammatory cytokines. The purposes of this study were to determine whether distinct latent classes of patients with breast cancer (n = 398) could be identified based on their experience with this symptom cluster, whether patients in these latent classes differed on demographic and clinical characteristics and whether variations in cytokine genes were associated with latent class membership. Three distinct latent classes were identified: "all low" (61.0%), "low pain and high fatigue" (31.6%), "all high" (7.1%). Compared to patients in the all low class, patients in the all high class were significantly younger, had less education, were more likely to be non-White, had a lower annual income, were more likely to live alone, had a lower functional status, had a higher comorbidity score, and had more advanced disease. Significant associations were found between interleukin 6 (IL6) rs2069845, IL13 rs1295686, and tumor necrosis factor alpha rs18800610 and latent class membership. Findings suggest that variations in pro- and anti-inflammatory cytokine genes are associated with this symptom cluster in breast cancer patients.