Integrated genomics and proteomics define huntingtin CAG length-dependent networks in mice.

To gain insight into how mutant huntingtin (mHtt) CAG repeat length modifies Huntington's disease (HD) pathogenesis, we profiled mRNA in over 600 brain and peripheral tissue samples from HD knock-in mice with increasing CAG repeat lengths. We found repeat length-dependent transcriptional signatures to be prominent in the striatum, less so in cortex, and minimal in the liver. Coexpression network analyses revealed 13 striatal and 5 cortical modules that correlated highly with CAG length and age, and that were preserved in HD models and sometimes in patients. Top striatal modules implicated mHtt CAG length and age in graded impairment in the expression of identity genes for striatal medium spiny neurons and in dysregulation of cyclic AMP signaling, cell death and protocadherin genes. We used proteomics to confirm 790 genes and 5 striatal modules with CAG length-dependent dysregulation at the protein level, and validated 22 striatal module genes as modifiers of mHtt toxicities in vivo

Predictors of Medication Adherence and Blood Pressure Control among Saudi Hypertensive Patients Attending Primary Care Clinics: A Cross-Sectional Study

Purpose To assess the level of medication adherence and to investigate predictors of medication adherence and blood pressure control among hypertensive patients attending primary healthcare clinics in Makkah, Saudi Arabia. Patients and methods Hypertensive patients meeting the eligibility criteria were recruited from eight primary care clinics between January and May 2016 for this study. The patients completed Arabic version of Morisky Medication Adherence Scale (MMAS-8), an eight-item validated, self-reported measure to assess medication adherence. A structured data collection form was used to record patients’ sociodemographic, medical and medication data. Results Two hundred and four patients, of which 71.6% were females, participated in the study. Patients’ mean age was 59.1 (SD 12.2). The mean number of medication used by patients was 4.4 (SD 1.89). More than half (110; 54%) of the patients were non-adherent to their medications (MMAS score 65 years (OR 2.0 [95% CI: 1.0–4.2; P = 0.04]), and being diabetic (OR 0.25 [95% CI: 0.1–0.6; P = 0.04]) were found to be independent predictors of medication adherence. Conclusion Medication adherence is alarmingly low among hypertensive patients attending primary care clinics in Saudi Arabia which may partly explain observed poor blood pressure control. There is a clear need to educate patients about the importance of medication adherence and its impact on improving clinical outcomes. Future research should identify barriers to medication adherence among Saudi hypertensive patients

Towards actionable knowledge: A systematic analysis of mobile patient portal use

As the aging population grows, chronic illness increases, and our healthcare costs sharply increase, patient portals are positioned as a central component of patient engagement through the potential to change the physician-patient relationship and enable chronic disease self-management. A patient’s engagement in their healthcare contributes to improving health outcomes, and information technologies can support health engagement. In this chapter, we extend the existing literature by discovering design gaps for patient portals from a systematic analysis of negative users’ feedback from the actual use of patient portals. Specifically, we adopt a topic modeling approach, latent Dirichlet allocation (LDA) algorithm, to discover design gaps from online low rating user reviews of a common mobile patient portal, EPIC’s mychart. To validate the extracted gaps, we compared the results of LDA analysis with that of human analysis. Overall, the results revealed opportunities to improve collaboration and to enhance the design of portals intended for patient-centered care. Incorporating these changes may enable the technologies to have stronger position to influence health improvement and wellness