Biomedical subjects

Renee Taylor

Publications and source records attributed to Renee Taylor.

5 recordsLinked to original sources

PubMed2006

Gene expression correlates of unexplained fatigue.

Quantitative trait analysis (QTA) can be used to test whether the expression of a particular gene significantly correlates with some ordinal variable. To limit the number of false discoveries in the gene list, a multivariate permutation test can also be performed. The purpose of this study is to identify peripheral blood gene expression correlates of fatigue using quantitative trait analysis on gene expression data from 20,000 genes and fatigue traits measured using the multidimensional fatigue inventory (MFI). A total of 839 genes were statistically associated with fatigue measures. These mapped to biological pathways such as oxidative phosphorylation, gluconeogenesis, lipid metabolism, and several signal transduction pathways. However, more than 50% are not functionally annotated or associated with identified pathways. There is some overlap with genes implicated in other studies using differential gene expression. However, QTA allows detection of alterations that may not reach statistical significance in class comparison analyses, but which could contribute to disease pathophysiology. This study supports the use of phenotypic measures of chronic fatigue syndrome (CFS) and QTA as important for additional studies of this complex illness. Gene expression correlates of other phenotypic measures in the CFS Computational Challenge (C3) data set could be useful. Future studies of CFS should include as many precise measures of disease phenotype as is practical.

Adult↗

PubMed2006

Identifying illness parameters in fatiguing syndromes using classical projection methods.

OBJECTIVES: To examine the potential of multivariate projection methods in identifying common patterns of change in clinical and gene expression data that capture the illness state of subjects with unexplained fatigue and nonfatigued control participants. METHODS: Data for 111 female subjects was examined. A total of 59 indicators, including multidimensional fatigue inventory (MFI), medical outcome Short Form 36 (SF-36), Centers for Disease Control and Prevention (CDC) symptom inventory and cognitive response described illness. Partial least squares (PLS) was used to construct two feature spaces: one describing the symptom space from gene expression in peripheral blood mononuclear cells (PBMC) and one based on 117 clinical variables. Multiplicative scatter correction followed by quantile normalization was applied for trend removal and range adjustment of microarray data. Microarray quality was assessed using mean Pearson correlation between samples. Benjamini-Hochberg multiple testing criteria served to identify significantly expressed probes. RESULTS: A single common trend in 59 symptom constructs isolates of nonfatigued subjects from the overall group. This segregation is supported by two co-regulation patterns representing 10% of the overall microarray variation. Of the 39 principal contributors, the 17 probes annotated related to basic cellular processes involved in cell signaling, ion transport and immune system function. The single most influential gene was sestrin 1 (SESN1), supporting recent evidence of oxidative stress involvement in chronic fatigue syndrome (CFS). Dominant variables in the clinical feature space described heart rate variability (HRV) during sleep. Potassium and free thyroxine (T4) also figure prominently. CONCLUSION: Combining multiple symptom, gene or clinical variables into composite features provides better discrimination of the illness state than even the most influential variable used alone. Although the exact mechanism is unclear, results suggest a common link between oxidative stress, immune system dysfunction and potassium imbalance in CFS patients leading to impaired sympatho-vagal balance strongly reflected in abnormal HRV.

Adult↗

PubMed2006

Exploration of statistical dependence between illness parameters using the entropy correlation coefficient.

UNLABELLED: The entropy correlation coefficient (ECC) is a useful tool for measuring statistical dependence between variables. We employed this tool to search for pairs of variables that correlated in the chronic fatigue syndrome (CFS) Computational Challenge dataset. Highly related variables are candidates for data reduction, and novel relationships could lead to hypotheses regarding the pathogenesis of CFS. METHODS: Data for 130 female participants in the Wichita (KS, USA) clinical study [1] was coded into numerical values. Metric data was grouped using Gaussian mixture models; the number of groups was chosen using Bayesian information content. The pair-wise correlation between all variables was computed using the ECC. Significance was estimated from 1000 iterations of a permutation test and a threshold of 0.01 was used to identify significantly correlated variables. RESULTS: The five dimensions of multidimensional fatigue inventory (MFI) were all highly correlated with each other. Seven Short Form (SF)-36 measures, four CFS case-defining symptoms and the Zung self-rating depression scale all correlated with all MFI dimensions. No physiological variables correlate with more than one MFI dimension. MFI, SF-36, CDC symptom inventory, the Zung self-rating depression scale and three Cambridge Neuropsychological Test Automated Battery (CANTAB) measures are highly correlated with CFS disease status. DISCUSSION: Correlations between the five dimensions of MFI are expected since they are measured from the same instrument. The relationship between MFI and Zung depression index has been previously reported. MFI, SF-36, and Centers for Disease Control and Prevention (CDC) symptom inventory are used to classify CFS; it is not surprising that they are correlated with disease status. Only one of the three CANTAB measures that correlate with disease status has been previously found, indicating the ECC identifies relationships not found with other statistical tools. CONCLUSION: The ECC is a useful tool for measuring statistical dependence between variables in clinical and laboratory datasets. The ECC needs to be further studied to gain a better understanding of its meaning for clinical data.

Adult↗

PubMedDate not supplied

Antibiotic prescriptions associated with outpatient visits for acute upper respiratory tract infections among adult Medicaid recipients in North Carolina.

BACKGROUND: North Carolina and the southeastern United States have the highest antimicrobial resistance rates for common respiratory tract pathogens in the nation. The excessive use of antibiotics for common outpatient infections is a major contributing factor in the emergence of antibiotic resistant bacteria. OBJECTIVE: To estimate the prevalence of oral antibiotic treatment for acute, nonbacterial respiratory tract infections among adult Medicaid recipients in North Carolina, and to describe a pilot project aimed at reducing the prevalence of oral antibiotic treatment among this population. METHODS: Using administrative claims data, we identified 24,137 Medicaid recipients, aged 18 to 64 years, who made at least one outpatient physician visit for acute nasopharyngitis (ICD-9, 460.x), acute pharyngitis (462.x), acute upper respiratory infection (465.9), acute bronchitis (466.0), or influenza (487.1) between October 1, 2000, and March 29, 2001. We excluded adults with chronic bronchitis (ICD-9, 491.x), emphysema (492.x), asthma (493.x), or chronic obstructive pulmonary disease (496.x). Pharmacy claims data were used to identify oral antibiotic treatment that occurred within 5 days of the outpatient visit. RESULTS: Overall, 63% (n = 15,189) of Medicaid recipients who made at least one outpatient visit during the observation period for one of the study conditions had a prescription filled for an oral antibiotic within 5 days. Residence in a rural county (64% vs. urban, 61%, p < 0.01) and in the eastern region of the state (65% vs. western region, 59%, p < 0.01) was associated with receipt of an antibiotic. Compared with the other principal study diagnoses, patients with acute bronchitis (44% of all outpatient visits) were 2.88 (95% CI = 2.72, 3.05) times more likely to receive oral antibiotic treatment after multivariate adjustment. SUMMARY: The prevalence of oral antibiotic treatment among adult Medicaid beneficiaries diagnosed with nonspecific upper respiratory infections, colds, pharyngitis, bronchitis, and influenza is high and varies significantly across patient demographics and geography. Interventions to reduce antibiotic prescribing are needed to reduce the progression of antimicrobial resistance.

Administration, Oral↗

PubMedDate not supplied

Feasibility of a primary care intervention to decrease oral antibiotics for acute upper respiratory tract infections: A pilot study.

BACKGROUND: Antimicrobial resistance in common respiratory tract pathogens is a growing public health threat, especially in the southeastern United States. The excessive use of antibiotics for common infections is a major contributing factor in the emergence of antibiotic resistance. We report results from a multi-site outpatient pilot project in North Carolina to reduce antibiotic prescriptions for acute nonbacterial upper respiratory tract infections (URIs). METHODS: Primary care practices were provided education and symptom therapy kits for patients with URIs, as an alternative to antibiotics, in a project to reduce the overuse of antimicrobial therapy The feasibility of this approach was evaluated with interviews and surveys. A methodology for claims-based evaluation of intervention efficacy in reduction of antibiotics use was developed as part of this project. RESULTS: Of eight contacted practices, four agreed to participate and three participated fully. Physicians reported that symptom therapy kits were useful for patients with URIs and resulted in a meaningful change in antibiotic prescribing behaviors. A claims-based approach is a feasible and promising method to evaluate efficacy in subsequent post-pilot large-scale implementations. LIMITATIONS: Due to the small number of outpatient practices and the lack of controls in this pilot study, the efficacy of the intervention in reducing antibiotic use could not be determined. CONCLUSIONS: Education combined with symptom therapy kits as an alternative to oral antibiotics is a feasible intervention that warrants additional studies to evaluate the efficacy of this approach in the reduction of antibiotic use for URIs.

Administration, Oral↗