Influence of donor age on induced pluripotent stem cells

Induced pluripotent stem cells (iPSCs) are being pursued as a source of cells for autologous therapies, many of which will be aimed at aged patients. To explore the impact of age on iPSC quality, we produced iPSCs from blood cells of 16 donors aged 21-100. We find that iPSCs from older donors retain an epigenetic signature of age, which can be reduced through passaging. Clonal expansion via reprogramming also enables the discovery of somatic mutations present in individual donor cells, which are missed by bulk sequencing methods. We show that exomic mutations in iPSCs increase linearly with age, and all iPSC lines analyzed carry at least one gene-disrupting mutation, several of which have been associated with cancer or dysfunction. Unexpectedly, elderly donors (>90 yrs) harbor fewer mutations than predicted, likely due to a contracted blood progenitor pool. These studies establish that donor age is associated with an increased risk of abnormalities in iPSCs and will inform clinical development of reprogramming technology.

A framework for smartphone-enabled, patient-generated health data analysis

Background: Digital medicine and smartphone-enabled health technologies provide a novel source of human health and human biology data. However, in part due to its intricacies, few methods have been established to analyze and interpret data in this domain. We previously conducted a six-month interventional trial examining the efficacy of a comprehensive smartphone-based health monitoring program for individuals with chronic disease. This included 38 individuals with hypertension who recorded 6,290 blood pressure readings over the trial.

Methods: In the present study, we provide a hypothesis testing framework for unstructured time series data, typical of patient-generated mobile device data. We used a mixed model approach for unequally spaced repeated measures using autoregressive and generalized autoregressive models, and applied this to the blood pressure data generated in this trial.

Results: We were able to detect, roughly, a 2 mmHg decrease in both systolic and diastolic blood pressure over the course of the trial despite considerable intra- and inter-individual variation. Furthermore, by supplementing this finding by using a sequential analysis approach, we observed this result over three months prior to the official study end—highlighting the effectiveness of leveraging the digital nature of this data source to form timely conclusions.

Conclusions: Health data generated through the use of smartphones and other mobile devices allow individuals the opportunity to make informed health decisions, and provide researchers the opportunity to address innovative health and biology questions. The hypothesis testing framework we present can be applied in future studies utilizing digital medicine technology or implemented in the technology itself to support the quantified self.

Bivalirudin vs Heparin in Percutaneous Coronary Intervention: A Pooled Analysis

Objective: This study evaluates outcomes with bivalirudin vs heparin in various patient subgroups and the overall population during percutaneous coronary interventions (PCI). Background: Recent data suggest that bivalirudin, a reversible direct thrombin inhibitor, provides ischemic protection superior to heparin and comparable to heparin plus glycoprotein (GP) IIb/IIIa inhibitors but with significantly fewer bleeding complications. Whether this advantage persists in different subgroups has not been fully defined. To our knowledge, this is the largest pooled analysis of bivalirudin to date.

Methods: Four randomized controlled trials were identified that compared bivalirudin to heparin (with or without GP IIb/IIIa inhibitors) in PCI. The incidence of death, myocardial infarction (MI), revascularization, and major bleeding at 48 hours was compared between these two agents overall and in patients with and without diabetes mellitus, hypertension, renal insufficiency, and advanced age.

Results: The trials consisted of 11,638 patients (bivalirudin, 5,861; heparin, 5,777). There were no significant differences in patient characteristics between the two groups. At 48 hours, the incidence of death, MI, revascularization, and major bleeding was significantly reduced in the bivalirudin group (7.8% vs 1.08%, P < .001); individual ischemic end points were significantly reduced for death (0.01% vs 0.02%, P = .049) and revascularization (2.0% vs 2.7%, P = .02), with similar reductions for major bleeding (2.7% vs 5.8%, P < .001). Subgroup analysis was generally consistent with the overall findings.

Conclusion: This analysis further supports the superiority of bivalirudin compared with heparin. Bivalirudin provides excellent ischemic protection with a significant reduction of bleeding complications, even in high-risk subgroups.

Rationale and design of a home-based trial using wearable sensors to detect asymptomatic atrial fibrillation in a targeted population: The mHealth Screening To Prevent Strokes (mSToPS) trial

Efficient methods for screening populations for undiagnosed atrial fibrillation (AF) are needed to reduce its associated mortality, morbidity, and costs. The use of digital technologies, including wearable sensors and large health record data sets allowing for targeted outreach toward individuals at increased risk for AF, might allow for unprecedented opportunities for effective, economical screening. The trial's primary objective is to determine, in a real-world setting, whether using wearable sensors in a risk-targeted screening population can diagnose asymptomatic AF more effectively than routine care. Additional key objectives include (1) exploring 2 rhythm-monitoring strategies-electrocardiogram-based and exploratory pulse wave-based-for detection of new AF, and (2) comparing long-term clinical and resource outcomes among groups. In all, 2,100 Aetna members will be randomized 1:1 to either immediate or delayed monitoring, in which a wearable patch will capture a single-lead electrocardiogram during the first and last 2 weeks of a 4-month period beginning immediately or 4 months after enrollment, respectively. An observational, risk factor-matched control group (n = 4,000) will be developed from members who did not receive an invitation to participate. The primary end point is the incidence of new AF in the immediate- vs delayed-monitoring arms at the end of the 4-month monitoring period. Additional efficacy and safety end points will be captured at 1 and 3 years. The results of this digital medicine trial might benefit a substantial proportion of the population by helping identify and refine screening methods for undiagnosed AF.

Whole-Genome Sequencing of a Healthy Aging Cohort

Studies of long-lived individuals have revealed few genetic mechanisms for protection against age-associated disease. Therefore, we pursued genome sequencing of a related phenotype-healthy aging-to understand the genetics of disease-free aging without medical intervention. In contrast with studies of exceptional longevity, usually focused on centenarians, healthy aging is not associated with known longevity variants, but is associated with reduced genetic susceptibility to Alzheimer and coronary artery disease. Additionally, healthy aging is not associated with a decreased rate of rare pathogenic variants, potentially indicating the presence of disease-resistance factors. In keeping with this possibility, we identify suggestive common and rare variant genetic associations implying that protection against cognitive decline is a genetic component of healthy aging. These findings, based on a relatively small cohort, require independent replication. Overall, our results suggest healthy aging is an overlapping but distinct phenotype from exceptional longevity that may be enriched with disease-protective genetic factors. VIDEO ABSTRACT.

Privacy and security in the era of digital health: what should translational researchers know and do about it?

The rapid growth in the availability and incorporation of digital technologies in almost every aspect of our lives creates extraordinary opportunities but brings with it unique challenges. This is especially true for the translational researcher, whose work has been markedly enhanced through the capabilities of big data aggregation and analytics, wireless sensors, online study enrollment, mobile engagement, and much more. At the same time each of these tools brings distinctive security and privacy issues that most translational researchers are inadequately prepared to deal with despite accepting overall responsibility for them. For the researcher, the solution for addressing these challenges is both simple and complex. Cyber-situational awareness is no longer a luxury-it is fundamental in combating both the elite and highly organized adversaries on the Internet as well as taking proactive steps to avoid a careless turn down the wrong digital dark alley. The researcher, now responsible for elements that may/may not be beyond his or her direct control, needs an additional level of cyber literacy to understand the responsibilities imposed on them as data owner. Responsibility lies with knowing what you can do about the things you can control and those you can't. The objective of this paper is to describe the data privacy and security concerns that translational researchers need to be aware of, and discuss the tools and techniques available to them to help minimize that risk.

A prospective randomized trial examining health care utilization in individuals using multiple smartphone-enabled biosensors

Background. Mobile health and digital medicine technologies are becoming increasingly used by individuals with common, chronic diseases to monitor their health. Numerous devices, sensors, and apps are available to patients and consumers-some of which have been shown to lead to improved health management and health outcomes. However, no randomized controlled trials have been conducted which examine health care costs, and most have failed to provide study participants with a truly comprehensive monitoring system. Methods. We conducted a prospective randomized controlled trial of adults who had submitted a 2012 health insurance claim associated with hypertension, diabetes, and/or cardiac arrhythmia. The intervention involved receipt of one or more mobile devices that corresponded to their condition(s) (hypertension: Withings Blood Pressure Monitor; diabetes: Sanofi iBGStar Blood Glucose Meter; arrhythmia: AliveCor Mobile ECG) and an iPhone with linked tracking applications for a period of 6 months; the control group received a standard disease management program. Moreover, intervention study participants received access to an online health management system which provided participants detailed device tracking information over the course of the study. This was a monitoring system designed by leveraging collaborations with device manufacturers, a connected health leader, health care provider, and employee wellness program-making it both unique and inclusive. We hypothesized that health resource utilization with respect to health insurance claims may be influenced by the monitoring intervention. We also examined health-self management. Results & Conclusions. There was little evidence of differences in health care costs or utilization as a result of the intervention. Furthermore, we found evidence that the control and intervention groups were equivalent with respect to most health care utilization outcomes. This result suggests there are not large short-term increases or decreases in health care costs or utilization associated with monitoring chronic health conditions using mobile health or digital medicine technologies. Among secondary outcomes there was some evidence of improvement in health self-management which was characterized by a decrease in the propensity to view health status as due to chance factors in the intervention group.

The emerging field of mobile health

The surge in computing power and mobile connectivity have fashioned a foundation for mobile health (mHealth) technologies that can transform the mode and quality of clinical research and health care on a global scale. Unimpeded by geographical boundaries, smartphone-linked wearable sensors, point-of-need diagnostic devices, and medical-grade imaging, all built around real-time data streams and supported by automated clinical decision-support tools, will enable care and enhance our understanding of physiological variability. However, the path to mHealth incorporation into clinical care is fraught with challenges. We currently lack high-quality evidence that supports the adoption of many new technologies and have financial, regulatory, and security hurdles to overcome. Fortunately, sweeping efforts are under way to establish the true capabilities and value of the evolving mHealth field.

Moving From Digitalization to Digitization in Cardiovascular Care: Why Is it Important, and What Could it Mean for Patients and Providers?

So far, the digitization of health care is best exemplified by electronic medical records, which have been far from favorably or uniformly accepted. However, properly implemented digitization can enable better patient outcomes, improve convenience, potentially lower healthcare costs, and possibly lead to much greater physician satisfaction. Precision (also known as personalized or individualized) medicine is frequently discussed today, but, in reality, it is what physicians have attempted to do as best they could for millennia. But now we have new tools that can begin to give us a much more high-definition view of our patients; from affordable and rapid genetic testing to wearable sensors that track a wide range of important physiologic parameters continuously. Although seemingly counterintuitive, the digitization of health care can also markedly improve the physician-patient relationship, allowing more time for human interaction when care is bolstered by digital technologies that better individualize diagnostics and treatments.

How Consumers and Physicians View New Medical Technology: Comparative Survey

Background

As a result of the digital revolution coming to medicine, a number of new tools are becoming available and are starting to be introduced in clinical practice.

Objective

We aim to assess health care professional and consumer attitudes toward new medical technology including smartphones, genetic testing, privacy, and patient-accessible electronic health records.

Methods

We performed a survey with 1406 health care providers and 1102 consumer responders.

Results

Consumers who completed the survey were more likely to prefer new technologies for a medical diagnosis (437/1102, 39.66%) compared with providers (194/1406, 13.80%; P<.001), with more providers (393/1406, 27.95%) than consumers (175/1102, 15.88%) reporting feeling uneasy about using technology for a diagnosis. Both providers and consumers supported genetic testing for various purposes, with providers (1234/1406, 87.77%) being significantly more likely than consumers (806/1102, 73.14%) to support genetic testing when planning to have a baby (P<.001). Similarly, 91.68% (1289/1406) of providers and 81.22% (895/1102) of consumers supported diagnosing problems in a fetus (P<.001). Among providers, 90.33% (1270/1406) were concerned that patients would experience anxiety after accessing health records, and 81.95% (1149/1406) felt it would lead to requests for unnecessary medical evaluations, but only 34.30% (378/1102; P<.001) and 24.59% (271/1102; P<.001) of consumers expressed the same concerns, respectively. Physicians (137/827, 16.6%) reported less concern about the use of technology for diagnosis compared to medical students (21/235, 8.9%; P=.03) and also more frequently felt that patients owned their medical record (323/827, 39.1%; and 30/235, 12.8%, respectively; P<.001).

Conclusions

Consumers and health professionals differ significantly and broadly in their views of emerging medical technology, with more enthusiasm and support expressed by consumers.