Vascular endothelial-cadherin as a marker of endothelial injury in preclinical Alzheimer disease.

OBJECTIVE: Endothelial dysfunction is an early and prevalent pathology in Alzheimer disease (AD). We here investigate the value of vascular endothelial-cadherin (VEC) as a cerebrospinal fluid (CSF) marker of endothelial injury in preclinical AD. METHODS: Cognitively normal participants (Clinical Dementia Rating [CDR] 0) from the Knight Washington University-ADRC were included in this study (n = 700). Preclinical Alzheimer's Cognitive Composite (PACC) scores, CSF VEC, tau, p-tau181, Aß42/Aß40, neurofilament light-chain (NFL) levels, and magnetic resonance imaging (MRI) assessments of white matter injury (WMI) were obtained from all participants. A subset of participants underwent brain amyloid imaging using positron emission tomography (amyloid-PET) (n = 534). Linear regression examined associations of CSF VEC with PACC and individual cognitive scores in preclinical AD. Mediation analyses examined whether CSF VEC mediated effects of CSF amyloid and tau markers on cognition in preclinical AD. RESULTS: CSF VEC levels significantly correlated with PACC and individual cognitive scores in participants with amyloid (A+T±N±; n = 558) or those with amyloid and tau pathologies (A+T+N±; n = 259), after adjusting for covariates. CSF VEC also correlated with CSF measures of amyloid, tau, and neurodegeneration and global amyloid burden on amyloid-PET scans in our cohort. Importantly, our findings suggest that CSF VEC mediates associations of CSF Aß42/Aß40, p-tau181, and global amyloid burden with cognitive outcomes in preclinical AD. INTERPRETATION: Our results support the utility of CSF VEC as a marker of endothelial injury in AD and highlight the importance of endothelial injury as an early pathology that contributes to cognitive impairment in even the earliest preclinical stages.

Method to transfer Chinese hamster ovary (CHO) batch shake flask experiments to large-scale, computer-controlled fed-batch bioreactors.

Chinese hamster ovary (CHO) cell cultures in industry are most commonly conducted as fed-batch cultures in computer-controlled bioreactors, though most preliminary studies are conducted in fed-batch shake flasks. To improve comparability between bioreactor studies and shake flask studies, shake flask studies should be conducted as fed-batch. However, the smaller volumes and reduced control in shake flasks can impact pH and aeration, which leads to performance differences. Planning and awareness of these vessel and control differences can assist with experimental design as well as troubleshooting. This method will highlight several of the configuration and control issues that should be considered during the transitions from batch to fed-batch and shake flasks to bioreactors, as well as approaches to mitigate the differences. Furthermore, if significant differences occur between bioreactor and shake flask studies, approaches will be presented to isolate the main contributors for these differences.

A randomized trial Examining The Impact Of Communicating Genetic And Lifestyle Risks For Obesity.

OBJECTIVE: Genetic testing for obesity is available directly to consumers, yet little is understood about its behavioral impact and its added value to nongenetic risk communication efforts based on lifestyle factors. METHODS: A randomized trial examined the short-term impact of providing personalized obesity risk information, using a 2 × 2 factorial design. Participants were recruited from the Coriell Personalized Medicine Collaborative (CPMC) and randomized to receive (1) no risk information (control), (2) genetic risk, (3) lifestyle risk, or (4) combined genetic/lifestyle risks. Baseline and 3-month follow-up survey data were collected. Analyses examined the impact of risk feedback on intentions to lose weight and self-reported weight. RESULTS: A total of 696 participants completed the study. A significant interaction effect was observed for genetic and lifestyle information on intent to lose weight (P = 0.0150). Those who received genetic risk alone had greater intentions at follow-up, compared with controls (P = 0.0034). The impact of receiving elevated risk information on intentions varied by source and combination of risks presented. Non-elevated genetic risk did not lower intentions. No group differences were observed for self-reported weight. CONCLUSIONS: Genetic risk information for obesity may add value to lifestyle risk information depending on the context in which it is presented.

An expanded pharmacogenomics warfarin dosing table with utility in generalised dosing guidance.

Pharmacogenomics (PGx) guided warfarin dosing, using a comprehensive dosing algorithm, is expected to improve dose optimisation and lower the risk of adverse drug reactions. As a complementary tool, a simple genotype-dosing table, such as in the US Food and Drug Administration (FDA) Coumadin drug label, may be utilised for general risk assessment of likely over- or under-anticoagulation on a standard dose of warfarin. This tool may be used as part of the clinical decision support for the interpretation of genetic data, serving as a first step in the anticoagulation therapy decision making process. Here we used a publicly available warfarin dosing calculator (www.warfarindosing.org) to create an expanded gene-based warfarin dosing table, the CPMC-WD table that includes nine genetic variants in CYP2C9, VKORC1, and CYP4F2. Using two datasets, a European American cohort (EUA, n=73) and the Quebec Warfarin Cohort (QWC, n=769), we show that the CPMC-WD table more accurately predicts therapeutic dose than the FDA table (51 % vs 33 %, respectively, in the EUA, McNemar's two-sided p=0.02; 52 % vs 37 % in the QWC, p<1×10(-6)). It also outperforms both the standard of care 5 mg/day dosing (51 % vs 34 % in the EUA, p=0.04; 52 % vs 31 % in the QWC, p<1×10(-6)) as well as a clinical-only algorithm (51 % vs 38 % in the EUA, trend p=0.11; 52 % vs 45 % in the QWC, p=0.003). This table offers a valuable update to the PGx dosing guideline in the drug label.

Genetic Knowledge Among Participants in the Coriell Personalized Medicine Collaborative.

Genetic literacy is essential for the effective integration of genomic information into healthcare; yet few recent studies have been conducted to assess the current state of this knowledge base. Participants in the Coriell Personalized Medicine Collaborative (CPMC), a prospective study assessing the impact of personalized genetic risk reports for complex diseases and drug response on behavior and health outcomes, completed genetic knowledge questionnaires and other surveys through an online portal. To assess the association between genetic knowledge and genetic education background, multivariate linear regression was performed. 4 062 participants completed a genetic knowledge and genetic education background questionnaire. Most were older (mean age: 50), Caucasian (90 %), female (59 %), highly educated (69 % bachelor's or higher), with annual household income over $100 000 (49 %). Mean percent correct was 76 %. Controlling for demographics revealed that health care providers, participants previously exposed to genetics, and participants with 'better than most' self-rated knowledge were significantly more likely to have a higher knowledge score (p < 0.001). Overall, genetic knowledge was high with previous genetic education experience predictive of higher genetic knowledge score. Education is likely to improve genetic literacy, an important component to expanded use of genomics in personalized medicine.

Using the Coriell Personalized Medicine Collaborative Data to conduct a genome-wide association study of sleep duration.

Sleep is critical to health and functionality, and several studies have investigated the inherited component of insomnia and other sleep disorders using genome-wide association studies (GWAS). However, genome-wide studies focused on sleep duration are less common. Here, we used data from participants in the Coriell Personalized Medicine Collaborative (CPMC) (n = 4,401) to examine putative associations between self-reported sleep duration, demographic and lifestyle variables, and genome-wide single nucleotide polymorphism (SNP) data to better understand genetic contributions to variation in sleep duration. We employed stepwise ordered logistic regression to select our model and retained the following predictive variables: age, gender, weight, physical activity, physical activity at work, smoking status, alcohol consumption, ethnicity, and ancestry (as measured by principal components analysis) in our association testing. Several of our strongest candidate genes were previously identified in GWAS related to sleep duration (TSHZ2, ABCC9, FBXO15) and narcolepsy (NFATC2, SALL4). In addition, we have identified novel candidate genes for involvement in sleep duration including SORCS1 and ELOVL2. Our results demonstrate that the self-reported data collected through the CPMC are robust, and our genome-wide association analysis has identified novel candidate genes involved in sleep duration. More generally, this study contributes to a better understanding of the complexity of human sleep.

Common genetic risk for melanoma encourages preventive behavior change.

There is currently great interest in using genetic risk estimates for common disease in personalized healthcare. Here we assess melanoma risk-related preventive behavioral change in the context of the Coriell Personalized Medicine Collaborative (CPMC). As part of on-going reporting activities within the project, participants received a personalized risk assessment including information related to their own self-reported family history of melanoma and a genetic risk variant showing a moderate effect size (1.7, 3.0 respectively for heterozygous and homozygous individuals). Participants who opted to view their report were sent an optional outcome survey assessing risk perception and behavioral change in the months that followed. Participants that report family history risk, genetic risk, or both risk factors for melanoma were significantly more likely to increase skin cancer preventive behaviors when compared to participants with neither risk factor (ORs = 2.04, 2.79, 4.06 and p-values = 0.02, 2.86 × 10-5, 4.67 × 10-5, respectively), and we found the relationship between risk information and behavior to be partially mediated by anxiety. Genomic risk assessments appear to encourage positive behavioral change in a manner that is complementary to family history risk information and therefore may represent a useful addition to standard of care for melanoma prevention.

Personalized genomic results: analysis of informational needs.

Use of genomic information in healthcare is increasing; however data on the needs of consumers of genomic information is limited. The Coriell Personalized Medicine Collaborative (CPMC) is a longitudinal study investigating the utility of personalized medicine. Participants receive results reflecting risk of common complex conditions and drug-gene pairs deemed actionable by an external review board. To explore the needs of individuals receiving genomic information we reviewed all genetic counseling sessions with CPMC participants. A retrospective qualitative review of notes from 157 genetic counseling inquiries was conducted. Notes were coded for salient themes. Five primary themes; "understanding risk", "basic genetics", "complex disease genetics", "what do I do now?" and "other" were identified. Further review revealed that participants had difficulty with basic genetic concepts, confused relative and absolute risks, and attributed too high a risk burden to individual single nucleotide polymorphisms (SNPs). Despite these hurdles, counseled participants recognized that behavior changes could potentially mitigate risk and there were few comments alluding to an overly deterministic or fatalistic interpretation of results. Participants appeared to recognize the multifactorial nature of the diseases for which results were provided; however education to understand the complexities of genomic risk information was often needed.

Image-guided resection of high-grade glioma: patient selection factors and outcome.

OBJECT: In patients with glioma, image-guided surgery helps to define the radiographic limits of the tumor to maximize safety and the extent of resection while minimizing damage to eloquent brain tissue. The authors hypothesize that image-guided resection (IGR) techniques are associated with improved outcomes in patients with malignant glioma. METHODS: Data recorded in 486 patients enrolled in the Glioma Outcomes Project were analyzed in this study. Demographic data and outcomes in patients who underwent IGR were compared with those in patients who underwent resection without IGR. Univariate analysis performed with chi-square testing was used to compare patient presentation, tumor characteristics, and death rates. Multivariate logistic regression was used to predict various outcome parameters. Patients who underwent IGR were younger and had smaller, lower-grade tumors than those in whom IGR was not performed. They were more likely to present with seizure and normal consciousness. Unexpectedly, gross-total resection was performed in significantly fewer patients with IGR than in individuals without IGR. Patients with IGR were more likely to be discharged home with the ability to live independently, and they had a shorter duration of hospital stay than patients without IGR. Survival was significantly longer in patients who underwent IGR, but multivariate analysis showed that glioblastoma multiforme (GBM) and age accounted for these observations. CONCLUSIONS: Selection bias occurs regarding patients who receive IGR; these biases include younger age, presentation with seizure and normal level of consciousness, tumor diameter less than 4 cm, and non-GBM on histopathological studies. Outcome appears to be improved in patients who undergo IGRs of high-grade gliomas. It is unclear if these improved outcomes are due to the selection of a more favorable patient population or to the IGR techniques themselves. It is likely that the full potential of image guidance in glioma surgery will not be realized until it is applied to a wider range of patients.

Baseline characteristics, management practices, and in-hospital outcomes of patients hospitalized with acute coronary syndromes in the Global Registry of Acute Coronary Events (GRACE).

Acute coronary syndrome (ACS) represents a heterogenous spectrum of conditions. The Global Registry of Acute Coronary Events (GRACE) describes the epidemiology, management, and outcomes of patients with ACS. Data were collected from 11,543 patients enrolled in 14 countries. Of these patients, 30% had ST-segment elevation myocardial infarction (STEMI), 25% had non-ST-segment elevation myocardial infarction (NSTEMI), 38% had unstable angina pectoris, and 7% had other cardiac or noncardiac diagnoses. Over half of these patients (53%) were >/=65 years old. Reperfusion therapy was used in 62% of patients with STEMI. Percutaneous coronary intervention was performed in 40% of these subjects during the index admission. Intravenous glycoprotein IIb/IIIa blockers were used in 23%, 20%, and 7% of patients with STEMI, NSTEMI, and unstable angina, respectively (STEMI vs NSTEMI, p = 0.0018, and for either group vs unstable angina, p <0.001). Coronary artery bypass grafting was performed in 4%, 10%, and 5% of patients, respectively (p <0.0001). Hospital case fatality rates were markedly different among patients with STEMI, NSTEMI, and unstable angina (7%, 6%, and 3%, respectively; STEMI vs NSTEMI, p = 0.0459, and for either group vs unstable angina, p <0.001). Congestive heart failure complicated the hospital course in 18%, 18%, and 10% of the patients, respectively (p <0.0001), and recurrent angina with ST-segment changes occurred before discharge in 10%, 10%, and 9% of patients, respectively (p = 0.2644). GRACE provides a detailed and comprehensive global description of the spectrum of patients with ACS.

Clinical trial participation among patients enrolled in the Glioma Outcomes Project.

BACKGROUND: Patient participation in well-designed and conducted clinical trials enables researchers to test new therapies. An understanding of the variables that possibly influence patient enrollment may help in patient recruitment for future trials. The authors evaluated factors that influenced patient enrollment in clinical trials using a prospective, large, multi-institutional registry of patients with malignant glioma. METHODS: Data were examined from 708 patients who underwent first or second surgery for a malignant glioma who were enrolled in the Glioma Outcomes Project, which is a prospective observational data base that captures clinical practice patterns. The frequency of clinical trial participation and the variables that may have been associated with trial participation were evaluated. These variables included age, gender, race, household income, educational level, first versus second craniotomy, histology, and whether the patient was treated at an academic institution. RESULTS: One hundred fifty-one of 708 patients (21.3%) participated in a clinical trial, which was higher than the participation reported typically for patients with other types of primary malignancies. In univariate analysis, race, histology, and first craniotomy were significant between the two groups, with Caucasian patients and patients with glioblastoma histology showing higher participation rates. In a multivariate logistic regression model, significant predictors included young age and glioblastoma multiforme histology. CONCLUSIONS: The authors present information on factors that may influence clinical trial participation among patients with malignant glioma and compare their data with information described previously on patients with other types of malignant disease. The percent of participation among the patients in the current study was greater than among patients with other primary tumor sites. Strategies should be implemented to improve recruitment to neuro-oncology trials, especially in elderly and minority populations.