Functional assay-based classification of PMS2 variants in Lynch Syndrome

The large majority of germline alterations identified in the DNA mismatch repair (MMR) gene PMS2, a low-penetrance gene for the cancer predisposition Lynch Syndrome (LS, OMIM 120435), represent variants of unknown significance (VUS). The inability to assess pathogenicity of such VUS interferes with personalized healthcare. The complete in vitro MMR activity (CIMRA) assay, that only requires sequence information on the VUS, provides a functional analysis-based tool suited for VUS classification. To derive a formula that translates CIMRA assay results for PMS2 VUS into the odds of pathogenicity (OddsPath), we used a set of clinically classified PMS2 variants, supplemented by inactivating variants generated by an in cellulo genetic screen, as proxies for pathogenic variants. Validation of this OddsPath revealed very high predictive values for PMS2 VUS. We conclude that this OddsPath provides an integral metric that, similar to the other, higher penetrance, MMR proteins MSH2, MLH1 and MSH6, can be incorporated into the upcoming criteria for MMR gene VUS classification of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP). This will represent a seminal step forward in enabling personalized healthcare for individuals suspected of LS and their relatives.

Thematic Dynamics of Internet of Things (IoT): Impact on Digital Personalized Healthcare (PHC)

Background: Information technology has continued to shape contemporary thematic trends. Advances in communication have impacted almost all themes ranging from education, engineering, healthcare, and many other aspects of our daily lives. Method: This paper attempts to review the different dynamics of the thematic IoT platforms. A select number of themes are extensively analyzed with emphasis on data mining (DM), personalized healthcare (PHC), and thematic trends of a select number of subjectively identified IoT-related publications over three years. In this paper, the number of IoT-related-publications is used as a proxy representing the number of apps. DM remains the trailblazer, serving as a theme with crosscutting qualities that drive artificial intelligence (AI), machine learning (ML), and data transformation. A case study in PHC illustrates the importance, complexity, productivity optimization, and nuances contributing to a successful IoT platform. Among the initial 99 IoT themes, 18 are extensively analyzed using the number of IoT publications to demonstrate a combination of different thematic dynamics, including subtleties that influence escalating IoT publication themes. Results: Based on findings amongst the 99 themes, the annual median IoT-related publications for all the themes over the four years were increasingly 5510, 8930, 11700, and 14800 for 2016, 2017, 2018, and 2019 respectively; indicating an upbeat prognosis of IoT dynamics. Conclusion: The vulnerabilities that come with the successful implementation of IoT systems are highlighted including the successes currently achieved by institutions promoting the benefits of IoT-related systems like the case study. Security continues to be an issue of significant importance.

Thematic Dynamics of Internet of Things (IoT): Impact on Digital Personalized Healthcare (PHC)

Information technology has continued to shape contemporary thematic trends. Advances in communication have impacted almost all themes ranging from education, engineering, healthcare, and many other aspects of our daily lives. This paper attempts to review the different dynamics of the thematic IoT platforms. A select number of themes are extensively analyzed with emphasis on data mining (DM), personalized healthcare (PHC), and thematic trends of a select number of subjectively identified IoT-related publications over three years. In this paper, the number of IoT-related-publications is used as a proxy representing the number of apps. DM remains the trailblazer, serving as a theme with crosscutting qualities that drive artificial intelligence (AI), machine learning (ML), and data transformation. A case study in PHC illustrates the importance, complexity, productivity optimization, and nuances contributing to a successful IoT platform. Among the initial 99 IoT themes, 18 are extensively analyzed using the number of IoT publications to demonstrate a combination of different thematic dynamics, including subtleties that influence escalating IoT publication themes. Based on findings amongst the 99 themes, the annual median IoT-related publications for all the themes over the four years were increasingly 5510, 8930, 11700, and 14800 for 2016, 2017, 2018, and 2019 respectively; indicating an upbeat prognosis of IoT dynamics. And finally, the vulnerabilities that come with the successful implementation of IoT systems are highlighted as part of the research. Security continues to be an issue of significant importance.

Taking control of your own pervasive mHealth Data: A Proof of Concept using a configurable Blockchain and mHealth application on iOS and Android devices (Preprint)

BACKGROUND Background: Blockchains offer a promising new distributed technology to address the challenges of data standardization, system interoperability, security, privacy, and accessibility for all data. However, integrating pervasive computing with blockchain’s ability to store privacy-protected mHealth data while providing HIPAA compliance is a challenge. Patients use a multitude of devices, apps, and services to collect and store mHealth data. Before the advent of blockchains, providing anonymized privacy controlled single point of access for different data sources for each user was a challenging problem. We present the design of an IoT-based configurable blockchain with different mHealth applications on iOS and Android collecting the same user’s data. We discuss the advantages of using such a blockchain architecture and demonstrate two things – the ease with which users can retain full control of their pervasive mHealth data and the ease with which HIPAA compliance can be accomplished by provider(s) who choose to access user data. We also allude to the future of shareable and tradeable data with our paper. OBJECTIVE Objective: The purpose of this paper is to design, evaluate and test IoT-based mHealth data using wearable devices using an efficient configurable blockchain designed and implemented ground up to store such data. The purpose of this paper is to demonstrate the privacy-preserving and HIPAA-compliant nature of pervasive computing-based personalized healthcare systems that give users total control of their own data. METHODS Methods: This paper followed the methodical design science approach adapted in information systems wherein we evaluate prior designs, propose enhancements with a Blockchain design pattern published by the same author(s), and use the design to support IoT transactions. We prototype both the blockchain and the IoT-based mHealth applications in different devices and test all use cases that formed the design goals for such a system. Specifically, we validate the design goals for our system using the HIPAA checklist for businesses and prove compliance of our architecture for mHealth data on pervasive computing devices. RESULTS Results: Blockchain-based personalized healthcare systems provide several advantages over traditional systems. They support the following features: provide and support extreme privacy protection, ability to share personalized data, provide the ability to delete data upon request, and support the ability to work on data. CONCLUSIONS Conclusions: We conclude that blockchain(s) and specifically the CHASM architecture presented in this paper, with configurable module(s) and a Software as a service Model provide many advantages for patients using pervasive devices that store mHealth data on the blockchain. Among them, is the ability to store, retrieve and modify one(s) generated healthcare data with a single private key across devices. This data is transparent and stored perennially and provides patients the privacy and pseudo-anonymity in addition to very strong encryption for data access. Firms and Device manufacturers would be benefited from such an approach wherein they relinquish user data control, while giving users the ability to select and offer their own mHealth data on data marketplaces. We show that such an architecture complies with the stringent requirements of HIPAA for patient data access.