PatientMatcher: a customizable Python-based open-source tool for matching undiagnosed rare disease patients via the MatchMaker Exchange network

The amount of data available from genomic medicine has revolutionized the approach to identify the determinants underlying many rare diseases. The task of confirming a genotype-phenotype causality for a patient affected with a rare genetic disease is often challenging. In this context, the establishment of the MatchMaker Exchange (MME) network has assumed a pivotal role in bridging heterogeneous patient information stored on different medical and research servers. MME has made it possible to solve rare disease cases by “matching” the genotypic and phenotypic characteristics of a patient of interest with patient data available at other clinical facilities participating in the network. Here, we present PatientMatcher (https://github.com/Clinical-Genomics/patientMatcher), an open-source Python and MongoDB-based software solution developed by Clinical Genomics facility at the Science for Life Laboratory in Stockholm. PatientMatcher is designed as a standalone MME server, but can easily communicate via REST API with external applications managing genetic analyses and patient data. The MME node is being implemented in clinical production in collaboration with the Genomic Medicine Center Karolinska at the Karolinska University Hospital. PatientMatcher is written to implement the MME API and provides several customizable settings, including a custom-fit similarity score algorithm and adjustable matching results notifications.

Cloud-based genomics pipelines for ophthalmology: reviewed from research to clinical practice

Aim: To familiarize clinicians with clinical genomics, and to describe the potential of cloud computing for enabling the future routine use of genomics in eye hospital settings.Design: Review article exploring the potential for cloud-based genomic pipelines in eye hospitals.Methods: Narrative review of the literature relevant to clinical genomics and cloud computing, using PubMed and Google Scholar. A broad overview of these fields is provided, followed by key examples of their integration.Results: Cloud computing could benefit clinical genomics due to scalability of resources, potentially lower costs, and ease of data sharing between multiple institutions. Challenges include complex pricing of services, costs from mistakes or experimentation, data security, and privacy concerns.Conclusions and future perspectives: Clinical genomics is likely to become more routinely used in clinical practice. Currently this is delivered in highly specialist centers. In the future, cloud computing could enable delivery of clinical genomics services in non-specialist hospital settings, in a fast, cost-effective way, whilst enhancing collaboration between clinical and research teams.

Clinical Functional Genomics

Functional genomics is the study of how the genome and its products, including RNA and proteins, function and interact to affect different biological processes. The field of functional genomics includes transcriptomics, proteomics, metabolomics and epigenomics, as these all relate to controlling the genome leading to expression of particular phenotypes. By studying whole genomes—clinical genomics, transcriptomes and epigenomes—functional genomics allows the exploration of the diverse relationship between genotype and phenotype, not only for humans as a species but also in individuals, allowing an understanding and evaluation of how the functional genome ‘contributes’ to different diseases. Functional variation in disease can help us better understand that disease, although it is currently limited in terms of ethnic diversity, and will ultimately give way to more personalized treatment plans.

Investigating equity in access to Australian clinical genetic health services for Aboriginal and Torres Strait Islander people

Globally, there is a recognised need for a greater commitment to an equity agenda in clinical genomics and precision medicine. Fundamental to this, is the equitable access by all to services providing genomic health care. However, achieving this remains constrained by a paucity of evidence that quantifies (in)equity of access to clinical genomics, particularly amongst Indigenous populations. Using administrative data from clinical genetic health services located in three jurisdictions (States/Territories) in Australia, we investigate equity in the scheduling and attendance of appointments among Aboriginal and/or Torres Strait Islander people, compared to non-Aboriginal and/or Torres Strait Islander people. For 15554 appointments scheduled between 2014-2018, adjusted Multivariate Poisson Regression models revealed that Aboriginal and/or Torres Strait Islander people were scheduled fewer appointments (IRR 0.73 [0.68-0.80], <0.001) and attended at lower rates (IRR 0.85 [0.78-0.93], <0.001). Within this population, adults, females, people living in remote locations, and those presenting in relation to cancer or prenatal indications experienced the greatest disparity in access. As the first quantitative, multi-jurisdictional study to measure access to clinical genetic health services, these results provide important baseline data related to the reach and equity of these services in Australia and contribute to the global effort to address equity in genomic health.

Clinical genomics in the 21st century: The fine balance between ethics and science

The 21st century has been revolutionary for the field of clinical genomics, with major advancements and breakthroughs over the years. It is now considered an instrumental tool in clinical and preventive medicine and has been used on a day-to-day basis to complement current clinical practice. However, with advancements in genomics comes greater bioethical concerns, which becomes increasingly complex with more cutting-edge technology. Some of the major ethical concerns include obtaining informed consent, possibility for genetic enhancements and eugenics, genomic equity and potential discrimination and cloning. It is imperative that we appreciate the benefits of genomic medicine in complementing traditional practices, identify and address the ethical concerns with relation to the practice of genomic medicine, and to ensure a common goal of improving human lives. With these in mind, the practice of genomics can have maximum impact in the collective health of the population, with greater benefit to all.