Search

Abstract Background Dendritic cells (DC) play a central role in primary immune responses and become potent stimulators of the adaptive immune response after undergoing the critical process of maturation. Understanding the dynamics of DC maturation would provide key insights into this important process. Time course microarray experiments can provide unique insights into DC maturation dynamics. Replicate experiments are necessary to address the issues of experimental and biological variability. Statistical methods and averaging are often used to identify significant signals. Here a novel strategy for filtering of replicate time course microarray data, which identifies consistent signals between the replicates, is presented and applied to a DC time course microarray experiment. Results The temporal dynamics of DC maturation were studied by stimulating DC with poly(I:C) and following gene expression at 5 time points from 1 to 24 hours. The novel filtering strategy uses standard statistical and fold change techniques, along with the consistency of replicate temporal profiles, to identify those differentially expressed genes that were consistent in two biological replicate experiments. To address the issue of cluster reproducibility a consensus clustering method, which identifies clusters of genes whose expression varies consistently between replicates, was also developed and applied. Analysis of the resulting clusters revealed many known and novel characteristics of DC maturation, such as the up-regulation of specific immune response pathways. Intriguingly, more genes were down-regulated than up-regulated. Results identify a more comprehensive program of down-regulation, including many genes involved in protein synthesis, metabolism, and housekeeping needed for maintenance of cellular integrity and metabolism. Conclusions The new filtering strategy emphasizes the importance of consistent and reproducible results when analyzing microarray data and utilizes consistency between replicate experiments as a criterion in both feature selection and clustering, without averaging or otherwise combining replicate data. Observation of a significant down-regulation program during DC maturation indicates that DC are preparing for cell death and provides a path to better understand the process. This new filtering strategy can be adapted for use in analyzing other large-scale time course data sets with replicates.

Abstract Background Temporal gene expression profiles characterize the time-dynamics of expression of specific genes and are increasingly collected in current gene expression experiments. In the analysis of experiments where gene expression is obtained over the life cycle, it is of interest to relate temporal patterns of gene expression associated with different developmental stages to each other to study patterns of long-term developmental gene regulation. We use tools from functional data analysis to study dynamic changes by relating temporal gene expression profiles of different developmental stages to each other. Results We demonstrate that functional regression methodology can pinpoint relationships that exist between temporary gene expression profiles for different life cycle phases and incorporates dimension reduction as needed for these high-dimensional data. By applying these tools, gene expression profiles for pupa and adult phases are found to be strongly related to the profiles of the same genes obtained during the embryo phase. Moreover, one can distinguish between gene groups that exhibit relationships with positive and others with negative associations between later life and embryonal expression profiles. Specifically, we find a positive relationship in expression for muscle development related genes, and a negative relationship for strictly maternal genes for Drosophila, using temporal gene expression profiles. Conclusion Our findings point to specific reactivation patterns of gene expression during the Drosophila life cycle which differ in characteristic ways between various gene groups. Functional regression emerges as a useful tool for relating gene expression patterns from different developmental stages, and avoids the problems with large numbers of parameters and multiple testing that affect alternative approaches.

Background: The U.S. POINTER study is a phase 3, multicenter, 2‐year randomized controlled trial (RCT) of two lifestyle interventions varying in intensity and format, conducted in older adults living in the U.S. who do not have objective cognitive impairment at study entry, but have increased risk of cognitive decline and dementia. Inclusion criteria included specific risk factors (e.g., family history of dementia, vascular risk factors) but not subjective cognitive concerns (SCCs). However, SCCs are likely to be common in this group of at‐risk individuals. U.S. POINTER provides a unique opportunity to evaluate the prevalence of SCCs and their demographic and clinical correlates in an at‐risk group. Methods: Recruitment for the U.S. POINTER study is still ongoing, and the following is based on a partial sample. The sample includes 1811 U.S. POINTER participants with complete baseline data (collected by December 2022), mean age = 68.2y (SD = 5.2), 73.5% are female, 70.2% have18+ years education, and 29.3% are from underrepresented groups. SCCs were measured by the brief 12‐item Everyday Cognition (ECog) questionnaire which includes two items in each of 6 domains: everyday memory, language, visuospatial abilities, planning, organization and divided attention. Responses on the ECog range from 0 = no change/better compared to baseline, 1 = questionably/inconsistently worse, 2 = consistently a little worse, 3 = much worse. Neuropsychological performance was measured using a global composite and episodic memory, executive functioning, and processing speed composites. Other variables included demographics, depression (Geriatric Depression Scale total score; GDS) and sleep (Insomnia severity index (ISI)) and vascular disease burden index. Results: Thirty‐five percent of the cohort endorsed having a subjective complaint on the ECog (score ≥2 on any item). The most frequent complaint was "Remembering where I have placed objects" (23%). SCCs did not differ by age, sex or education. ECog‐12 Total were related to insomnia and depression (p<.0001). After adjusting for age, sex, education, vascular risk burden, GDS and ISI, greater SCC (ECog‐12 Total) was still associated with the global composite and all three domains (ps < 0.003). Conclusions: SCCs, particularly everyday memory complaints, were relatively common in this at‐risk cohort. While SCCs were related to depression and sleep, they were also independently associated with slightly worse cognitive function. [ABSTRACT FROM AUTHOR]

Background: Cognitive dispersion refers to the within‐person variability across tasks. Relative to the normative approach, cognitive dispersion may be more sensitive to subtle changes in preclinical Alzheimer's disease. Greater dispersion has been associated with increased risk for conversion to mild cognitive impairment and faster rates of medial temporal lobe atrophy. This metric can be derived from a regular neuropsychological assessment and complement traditional outcome approaches, particularly in those underrepresented in normative data. This study evaluated cognitive dispersion as an independent predictor of clinical status across racial and ethnic groups. Method: Baseline data on 1811 cognitively unimpaired older adults with high vascular risk from the U.S. POINTER multisite lifestyle intervention study were examined. Sample characteristics included mean age of 68 (SD = 5.2), 70% female, 30% less‐than‐college education, and 29% underrepresented groups (301 Black, 231 Other). Correlations between cognitive dispersion and other brain health risks (vascular, subjective cognitive decline (SCD), physical activity) were tested. Cognitive dispersion was defined as the standard deviation of individuals' z‐transformed scores of 8 cognitive tests. Vascular risk burden was the sum of 5 conditions (hypertension, diabetes, hypercholesterolemia, heart disease, obesity). Self‐report SCD was measured by the Cognitive Function Instrument (CFI) and Measurement of Everyday Cognition (ECOG12). Logistic Regression Models were fitted to predict Clinical Dementia Global Ratings (CDR 0.5 vs. 0) to evaluate cognitive dispersion as an independent predictor in the whole sample, White participants and Black participants, controlled for demographics, vascular risk, and physical activity. Logistic Regression Models were also evaluated with CFI or ECOG12 as additional covariate. Result: Greater cognitive dispersion was correlated with older age, greater vascular burden and less physical activity, but not SCD. Cognitive dispersion was significantly higher in men, Black participants, and participants with less education. Cognitive dispersion predicted CDR in Black participants (OR = 4.7, p<0.01), and trended in the whole sample (OR = 1.6, p = 0.05), but was not significant in White participants (OR = 1.2, p = 0.63). Results hold when controlled for SCD (Table 1). Conclusion: Results supported cognitive dispersion as a sensitive objective metric, in addition to self‐report SCD, to identify individuals showing the earliest clinical signs of decline, particularly among those underrepresented in traditional norms. [ABSTRACT FROM AUTHOR]

We examine Internet use and eHealth literacy among older adults (aged 55+ years) who were patients at clinics serving low-income populations. Participants included 200 minority and White adults who completed interviews based on a technology acceptance conceptual model. A total of 106 participants (53.0%) used the Internet; utilization was associated with personal characteristics (age, ethnicity, education, poverty), computer characteristics (number of e-devices, computer stress), social support (marital status), and health knowledge and attitudes (health literacy, medical decision making, health information sources), but not health status. Of the 106 participants who used the Internet, 52 (49.1%) had high eHealth literacy; eHealth literacy was associated with computer characteristics (number of e-devices, computer stress), and health knowledge and attitudes (medical decision making, health information sources). In multivariate analysis, computer stress maintained a significant inverse association with eHealth literacy. Educational interventions to help older adults successfully use technology and improve eHealth literacy must be identified. [ABSTRACT FROM AUTHOR]

Background: Obesity compounds aging-related declines in cardiorespiratory fitness, with accompanying fatigue and disability. This study determined the effects of two different levels of caloric restriction (CR) during aerobic training on cardiorespiratory fitness, fatigue, physical function, and cardiometabolic risk.Methods: The INFINITE study was a 20-week randomized trial in 180 older (65-79 years) men and women with obesity (body mass index = 30-45 kg/m2). Participants were randomly assigned to (i) aerobic training (EX; treadmill 4 days/wk for 30 minutes at 65%-70% of heart rate reserve), (ii) EX with moderate (-250 kcal/d) CR (EX + Mod-CR), or (iii) EX with more intensive (-600 kcal/d) CR (EX + High-CR). Cardiorespiratory fitness (peak aerobic capacity, VO2 peak, primary outcome) was determined during a graded exercise test.Results: One hundred and fifty-five participants returned for 20-week data collection (87% retention). VO2 peak increased by 7.7% with EX, by 13.8% with EX + Mod-CR, and by 16.0% with EX + High-CR, and there was a significant treatment effect (EX + High-CR = 21.5 mL/kg/min, 95% confidence interval = 19.8-23.2; EX + Mod-CR = 21.2 mL/kg/min, 95% confidence interval = 19.4-23.0; EX = 20.1 mL/kg/min, 95% confidence interval = 18.4-21.9). Both CR groups exhibited significantly greater improvement in self-reported fatigue and disability and in glucose control, compared with EX.Conclusion: Combining aerobic exercise with even moderate CR is more efficacious for improving cardiorespiratory fitness, fatigue and disability, and glucose control than exercise alone and is as effective as higher-dose CR. [ABSTRACT FROM AUTHOR]

Background: Previous studies support beneficial effects of both resistance exercise training (RT) and caloric restriction (CR) on skeletal muscle strength and physical performance. The goal of this study was to determine the effects of adding CR to RT on single-muscle fiber contractility responses to RT in older overweight and obese adults.Methods: We analyzed contractile properties in 1,253 single myofiber from muscle biopsies of the vastus lateralis, as well as physical performance and thigh muscle volume, in 31 older (65-80 years), overweight or obese (body mass index = 27-35 kg/m2) men (n = 19) and women (n = 12) who were randomly assigned to a standardized, progressive RT intervention with CR (RT+CR; n = 15) or without CR (RT; n = 16) for 5 months.Results: Both interventions evoked an increase in force normalized to cross-sectional area (CSA), in type-I and type-II fibers and knee extensor quality. However, these improvements were not different between intervention groups. In the RT group, changes in total thigh fat volume inversely correlated with changes in type-II fiber force (r = -.691; p = .019). Within the RT+CR group, changes in gait speed correlated positively with changes in type-I fiber CSA (r = .561; p = .030). In addition, increases in type-I normalized fiber force were related to decreases in thigh intermuscular fat volume (r = -0.539; p = .038).Conclusion: Single muscle fiber force and knee extensor quality improve with RT and RT+CR; however, CR does not enhance improvements in single muscle fiber contractility or whole muscle in response to RT in older overweight and obese men and women. [ABSTRACT FROM AUTHOR]

Background: Cognitive impairment and decline may signal the increased risk of incident cardiovascular disease (CVD). We examined associations of global cognitive function, as measured by the Modified Mini-Mental State Examination (3MS) and changes in 3MS over time, with incident CVD, individual CVD outcomes, CVD death, and all-cause mortality.Methods: A total of 5,596 women (≥ 60) from the Women's Health Initiative Memory Study free of CVD at baseline were followed for an average of 7.1 years. The 3MS was measured at baseline and annually thereafter. Cox proportional hazards regressions were used to model associations between baseline 3MS and changes in 3MS and time to events.Results: In the fully-adjusted models for every 5-point lower baseline 3MS score, the risk was 12% greater for incident CVD, 37% for HF, 35% for CVD death, and 24% for all-cause mortality. No significant relationships were found for coronary heart disease (CHD), angina, stroke/transient ischemic attack (TIA), or coronary revascularization. When change in 3MS was added as a time-varying covariate in the fully-adjusted models, for every 1-point/year greater decline in 3MS, the risk was 4% greater for incident CVD, 10% for CHD, 9% for Stroke/TIA, 17% for CVD death, and 13% for all-cause mortality.Conclusions: In older women free of prevalent CVD at baseline, lower baseline global cognitive function or decline in global cognitive function over time, increased risk of incident CVD, CVD death, and all-cause mortality. [ABSTRACT FROM AUTHOR]

Background: The Women's Health Initiative has collected data on the aging process of postmenopausal women for over two decades, including data on many women who have achieved age 80 years and older. However, there has not been any previous effort to characterize the 80+ cohort and to identify associated retention factors.Methods: We include all women at baseline of the Women's Health Initiative who would be at least 80 years of age as of September 17, 2012. We summarize retention rates during the study and across two re-enrollment campaigns as well as the demographic and health-related characteristics that predicted retention. Further, we describe the longitudinal change from baseline in the women identified as members of the 80+ cohort.Results: Retention rates were lower during each of two re-enrollment periods (74% and 83% retained during re-enrollment periods 1 and 2, respectively) than during the first and second data collection periods (90% each). Women who were retained were more likely to be white, educated, and healthier at baseline. Women age 80 and older saw modest changes in body mass index and depression burden, despite lower physical activity and increased cardiovascular disease.Conclusions: The characteristics of women who were retained in the 80+ cohort differ in significant ways compared with their peers at baseline. Identifying the characteristics associated with attrition in older cohorts is important because aging and worsening health has a negative impact on study attrition. Strategies should be implemented to improve retention rates among less healthy older adults. [ABSTRACT FROM AUTHOR]