Distinct Transcriptome Expression of the Temporal Cortex of the Primate Microcebus murinus during Brain Aging versus Alzheimer's Disease-Like Pathology

Aging is the primary risk factor of neurodegenerative disorders such as Alzheimer's disease (AD). However, the molecular events occurring during brain aging are extremely complex and still largely unknown. For a better understanding of these age-associated modifications, animal models as close as possible to humans are needed. We thus analyzed the transcriptome of the temporal cortex of the primate Microcebus murinus using human oligonucleotide microarrays (Affymetrix). Gene expression profiles were assessed in the temporal cortex of 6 young adults, 10 healthy old animals and 2 old, “AD-like” animals that presented ß-amyloid plaques and cortical atrophy, which are pathognomonic signs of AD in humans. Gene expression data of the 14,911 genes that were detected in at least 3 samples were analyzed. By SAM (significance analysis of microarrays), we identified 47 genes that discriminated young from healthy old and “AD-like” animals. These findings were confirmed by principal component analysis (PCA). ANOVA of the expression data from the three groups identified 695 genes (including the 47 genes previously identified by SAM and PCA) with significant changes of expression in old and “AD-like” in comparison to young animals. About one third of these genes showed similar changes of expression in healthy aging and in “AD-like” animals, whereas more than two thirds showed opposite changes in these two groups in comparison to young animals. Hierarchical clustering analysis of the 695 markers indicated that each group had distinct expression profiles which characterized each group, especially the “AD-like” group. Functional categorization showed that most of the genes that were up-regulated in healthy old animals and down-regulated in “AD-like” animals belonged to metabolic pathways, particularly protein synthesis. These data suggest the existence of compensatory mechanisms during physiological brain aging that disappear in “AD-like” animals. These results open the way to new exploration of physiological and “AD-like” aging in primates

Predicting treatment course and outcome using a promotion and prevention framework in a community sample of arthritis sufferers

Dan V Blalock,1,2 Patrick E McKnight,3 Todd B Kashdan,3 Simone C Franz3,4 1Center for Health Services Research in Primary Care, Durham Veterans Affairs Medical Center, Durham, NC, USA; 2Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA; 3Department of Psychology, George Mason University, Fairfax, VA, USA; 4Humanproof, LLC, Arlington, VA, USA Objective: The present study examined the proposition that patients need to focus on something beyond simply “getting better”. In a sample of arthritis sufferers, we distinguished individuals by the goals that motivated them – moving toward aspirational goals and maximizing gains (promotion focus) rather than obligations and minimizing losses (prevention focus) – and how these motivational styles influenced treatment. Methods: Patients (N=254) participated in a randomized controlled trial of resistance training and self-management, providing 6 time points of data over 2 years. Promotion and prevention focus at baseline were used to predict the course (compliance and changes in coping self-efficacy) and outcome (changes in physical functioning) of treatment. Results: Arthritis sufferers with strong promotion orientations showed significant improvements in physical functioning (a direct positive impact on physical health); there were no significant associations with treatment compliance and coping self-efficacy. Arthritis sufferers with strong prevention orientations complied less with the treatment and showed little change in coping self-efficacy during treatment, which, in turn, predicted worse physical functioning over time (a pernicious, indirect influence on treatment outcome). Conclusion: A focus on positive approach-oriented goals may improve overall treatment response, whereas a focus on negative avoidance-oriented goals may degrade treatment response through reduced compliance and self-efficacy. Keywords: treatment, promotion and prevention, self-efficacy, physical functioning, arthriti

The new landscape of medication adherence improvement: where population health science meets precision medicine

Leah L Zullig,1,2 Dan V Blalock,1,3 Samantha Dougherty,4 Rochelle Henderson,5 Carolyn C Ha,4 Megan M Oakes,2 Hayden B Bosworth1–3,6 1Durham Center for Health Services Research in Primary Care, Durham Veterans Affairs Health Care System, Durham, NC, USA; 2Department of Population Health Sciences, Duke University, Durham, NC, USA; 3Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA; 4Pharmaceutical Research and Manufacturers of America, Washington, DC, USA; 5Express Scripts Holding Company, St Louis, MO, USA; 6School of Nursing, Duke University, Durham, NC, USA Abstract: Despite the known health and economic benefits of medications, nonadherence remains a significant, yet entirely preventable public health burden. Over decades, there have been numerous research studies evaluating health interventions and policy efforts aimed at improving adherence, yet no universal or consistently high impact solutions have been identified. At present, new challenges and opportunities in policy and the movement toward value-based care should foster an environment that appreciates adherence as a mechanism to improve health outcomes and control costs (eg, fewer hospitalizations, reduced health care utilization). Our objective was to provide a commentary on recent changes in the landscape of research and health policy directed toward improving adherence and an actionable agenda to achieve system level savings and improved health by harnessing the benefits of medications. Specifically, we address the complementary perspectives of precision medicine and population health management; integrating data sources to develop innovative measurement of adherence and target adherence interventions; and behavioral economics to determine appropriate incentives. Keywords: adherence, policy, precision medicine, population healt