Citations

Abstract BACKGROUND Interindividual variability in blood pressure (BP) response to antihypertensives has been reported. Although plasma renin activity (PRA) is a potential biomarker for personalizing antihypertensive therapy in European American (EA) and African American (AA) hypertensives, clinical utility of PRA-guided prescribing is incompletely understood. METHODS Using systematic-phased approach, PRA’s clinical utility was assessed. After categorizing by baseline PRA, clinic systolic BP (SBP) responses to metoprolol and chlorthalidone were compared in 134 EAs and 102 AAs enrolled in the Pharmacogenomics Evaluation of Antihypertensive Responses-2 (PEAR-2) trial. Receiver operating characteristic (ROC) analysis was conducted in EAs. Data from PEAR-2 AAs were used to estimate an optimal PRA cut point using multivariable linear regression models. The derived cut point in AAs was tested in a meta-analysis of 2 independent AA cohorts, and its sensitivity and specificity were assessed. RESULTS EAs with PRA < 0.65 ng/ml/hour had a greater decrease in SBP to chlorthalidone than metoprolol (by –15.9 mm Hg, adjusted P < 0.0001), whereas those with PRA ≥ 0.65 ng/ml/hour had a greater decrease in SBP to metoprolol than chlorthalidone (by 3.3 mm Hg, adjusted P = 0.04). Area under ROC curve (0.69, P = 0.0001) showed that PRA can predict SBP response among EAs. However, we observed no association between PRA and SBP response in PEAR-2 AAs. Among independent AA cohorts, those with PRA ≥ 1.3 ng/ml/hour (PEAR-2-derived cut point) responded better to atenolol/candesartan than hydrochlorothiazide (meta-analysis P = 0.01). However, sensitivity of the derived cut point was 10%. CONCLUSIONS PRA at the previously established 0.60–0.65 ng/ml/hour cut point is an effective predictive biomarker of BP response in EAs. However, we were unable to identify PRA cut point that could be used to guide antihypertensive selection in AAs. TRIAL REGISTRATION NCT01203852, NCT00246519, NCT00005520.

AbstractAlzheimer's disease (AD) is the most common type of dementia in the elderly with no effective treatment currently. Recent studies of noninvasive neuroimaging, resting‐state functional magnetic resonance imaging (rs‐fMRI) with graph theoretical analysis have shown that patients with AD and mild cognitive impairment (MCI) exhibit disrupted topological organization in large‐scale brain networks. In previous work, it is a common practice to threshold such networks. However, it is not only difficult to make a principled choice of threshold values, but also worse is the discard of potential important information. To address this issue, we propose a threshold‐free feature by integrating a prior persistent homology‐based topological feature (the zeroth Betti number) and a newly defined connected component aggregation cost feature to model brain networks over all possible scales. We show that the induced topological feature (Integrated Persistent Feature) follows a monotonically decreasing convergence function and further propose to use its slope as a concise and persistent brain network topological measure. We apply this measure to study rs‐fMRI data from the Alzheimer's Disease Neuroimaging Initiative and compare our approach with five other widely used graph measures across five parcellation schemes ranging from 90 to 1,024 region‐of‐interests. The experimental results demonstrate that the proposed network measure shows more statistical power and stronger robustness in group difference studies in that the absolute values of the proposed measure of AD are lower than MCI and much lower than normal controls, providing empirical evidence for decreased functional integration in AD dementia and MCI.

Abstract Introduction The overall goal of the Alzheimer's Disease Neuroimaging Initiative (ADNI) is to validate biomarkers for Alzheimer's disease (AD) clinical trials. ADNI is a multisite, longitudinal, observational study that has collected many biomarkers since 2004. Recent publications highlight the multifactorial nature of late‐onset AD. We discuss selected topics that provide insights into AD progression and outline how this knowledge may improve clinical trials. Methods We used standard methods to identify nearly 600 publications using ADNI data from 2016 and 2017 (listed in Supplementary Material and searchable at http://adni.loni.usc.edu/news‐publications/publications/ ). Results (1) Data‐driven AD progression models supported multifactorial interactions rather than a linear cascade of events. (2) β‐Amyloid (Aβ) deposition occurred concurrently with functional connectivity changes within the default mode network in preclinical subjects and was followed by specific and progressive disconnection of functional and anatomical networks. (3) Changes in functional connectivity, volumetric measures, regional hypometabolism, and cognition were detectable at subthreshold levels of Aβ deposition. 4. Tau positron emission tomography imaging studies detailed a specific temporal and spatial pattern of tau pathology dependent on prior Aβ deposition, and related to subsequent cognitive decline. 5. Clustering studies using a wide range of modalities consistently identified a “typical AD” subgroup and a second subgroup characterized by executive impairment and widespread cortical atrophy in preclinical and prodromal subjects. 6. Vascular pathology burden may act through both Aβ dependent and independent mechanisms to exacerbate AD progression. 7. The APOE ε4 allele interacted with cerebrovascular disease to impede Aβ clearance mechanisms. 8. Genetic approaches identified novel genetic risk factors involving a wide range of processes, and demonstrated shared genetic risk for AD and vascular disorders, as well as the temporal and regional pathological associations of established AD risk alleles. 9. Knowledge of early pathological changes guided the development of novel prognostic biomarkers for preclinical subjects. 10. Placebo populations of randomized controlled clinical trials had highly variable trajectories of cognitive change, underscoring the importance of subject selection and monitoring. 11. Selection criteria based on Aβ positivity, hippocampal volume, baseline cognitive/functional measures, and APOE ε4 status in combination with improved cognitive outcome measures were projected to decrease clinical trial duration and cost. 12. Multiple concurrent therapies targeting vascular health and other AD pathology in addition to Aβ may be more effective than single therapies. Discussion ADNI publications from 2016 and 2017 supported the idea of AD as a multifactorial disease and provided insights into the complexities of AD disease progression. These findings guided the development of novel biomarkers and suggested that subject selection on the basis of multiple factors may lower AD clinical trial costs and duration. The use of multiple concurrent therapies in these trials may prove more effective in reversing AD disease progression.

AbstractObjectiveThe established link between oestrogen and breast cancer occurs via both oestrogen receptor (ER)‐mediated and non ER‐mediated mechanisms. The term genotoxic estrogens describes mutagenic metabolites, including oestrogen catechols and quinones, which have been linked to breast carcinogenesis in post‐menopausal women. We aimed to assess whether the route of administration of 17β oestradiol (E2) affects the accumulation of genotoxic oestrogen metabolites in a model of ovarian failure in young girls with Turner syndrome.MethodsStored plasma samples obtained at 0 and 12 months were used from 40 adolescents with Turner syndrome who participated in a 12 months randomized controlled trial of the metabolic impact of E2 orally (2 mg/d) vs transdermally (100 µg/d); dose escalation allowed matching of unconjugated E2 levels in the parent study. We measured 12 oestrogen metabolites (total concentrations = conjugated and unconjugated) using a highly sensitive LCMSMS assay. Results from 48 normally menstruating adolescents were used for comparison.ResultsAfter treatment, least square mean (SE) total E2 concentrations were higher in the oral vs transdermal group (6784 pmol/L vs 1123 [1614], P < 0.0001), as was oestrone (E1) (91 060 pmol/L vs 19 278 [16 534], P < 0.0001). Also, higher after oral treatment were catechol‐oestrogens 4‐hydroxy‐E2 (149 vs 28 [±49] pmol/L), 2‐hydroxy‐E2 (300 vs 76 [±52]), 4‐hydroxy‐E1 (450 vs 105 [±113]), 2‐hydroxy‐E1 (3094 vs 740 [±684]) and 16α‐hydroxy‐E1 (3,007 vs 157 [±534]) (<0.001 between groups). Levels were much closer to controls in the transdermal group.ConclusionsCommon feminizing doses of oral oestradiol for 12 months result in substantial accumulation of unphysiologic, genotoxic oestrogens compared to transdermal oestradiol, expanding concerns about oral oestrogens’ first hepatic passage. Further studies assessing long‐term risks of these metabolites in women taking different forms of oestrogen are needed.

AbstractParenteral nutrition (PN) is a complex therapeutic modality provided to neonates, children, and adults for various indications. Surveys have shown that current electronic health record (EHR) systems are in need of functionality enhancement for safe and optimal delivery of PN. This is a consensus statement from the American Society for Parenteral and Enteral Nutrition, the Academy of Nutrition and Dietetics, and the American Society of Health‐System Pharmacists outlining some of the key challenges to prescribing, order review/verification, compounding, and administration of PN using EHRs today and is a call to action for clinicians and vendors to optimize their EHRs regarding the PN build and workflow.

AbstractParenteral nutrition (PN) is a complex therapeutic modality provided to neonates, children, and adults for various indications. Surveys have shown that current electronic health record (EHR) systems are in need of functionality enhancement for safe and optimal delivery of PN. This is a consensus statement from the American Society for Parenteral and Enteral Nutrition, the Academy of Nutrition and Dietetics, and the American Society of Health‐System Pharmacists outlining some of the key challenges to prescribing, order review/verification, compounding, and administration of PN using EHRs today and is a call to action for clinicians and vendors to optimize their EHRs regarding the PN build and workflow.