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Biology subjects

Arvai, K.

Publications and source records attributed to Arvai, K..

2 recordsLinked to original sources

Integrating healthcare and research genetic data empowers the discovery of 49 novel developmental disorders

De novo mutations (DNMs) in protein-coding genes are a well-established cause of developmental disorders (DD). However, known DD-associated genes only account for a minority of the observed excess of such DNMs. To identify novel DD-associated genes, we integrated healthcare and research exome sequences on 31,058 DD parent-offspring trios, and developed a simulation-based statistical test to identify gene-specific enrichments of DNMs. We identified 285 significantly DD-associated genes, including 28 not previously robustly associated with DDs. Despite detecting more DD-associated genes than in any previous study, much of the excess of DNMs of protein-coding genes remains unaccounted for. Modelling suggests that over 1,000 novel DD-associated genes await discovery, many of which are likely to be less penetrant than the currently known genes. Research access to clinical diagnostic datasets will be critical for completing the map of dominant DDs.

genomics↗

Open Humans: A platform for participant-centered research and personal data exploration

BackgroundMany aspects of our lives are now digitized and connected to the internet. As a result, individuals are now creating and collecting more personal data than ever before. This offers an unprecedented chance for human-participant research ranging from the social sciences to precision medicine. With this potential wealth of data come practical problems (such as how to merge data streams from various sources), as well as ethical problems (such as how to best balance risks and benefits when enabling personal data sharing by individuals).\n\nResultsTo begin to address these problems in real time, we present Open Humans, a community-based platform that enables personal data collections across data streams, giving individuals more personal data access and control of sharing authorizations, and enabling academic research as well as patient-led projects. We showcase data streams that Open Humans combines (e.g. personal genetic data, wearable activity monitors, GPS location records and continuous glucose monitor data), along with use cases of how the data facilitates various projects.\n\nConclusionsOpen Humans highlights how a community-centric ecosystem can be used to aggregate personal data from various sources as well as how these data can be used by academic and citizen scientists through practical, iterative approaches to sharing that strive to balance considerations with participant autonomy, inclusion, and privacy.

bioinformatics↗