Participant-driven matchmaking in the genomic era

An induced pluripotent stem cell-derived NMJ platform for study of the NGLY1-Congenital Disorder of Deglycosylation

There are many neurological rare diseases where animal models have proven inadequate or do not currently exist. NGLY1 Deficiency, a congenital disorder of deglycosylation, is a rare disease that predominantly affects motor control, especially control of neuromuscular action. In this study, NGLY1-deficient, patient-derived induced pluripotent stem cells (iPSCs) were differentiated into motoneurons (MNs) to identify disease phenotypes analogous to clinical disease pathology with significant deficits apparent in the NGLY1-deficient lines compared to the control. A neuromuscular junction (NMJ) model was developed using patient and wild type (WT) MNs to study functional differences between healthy and diseased NMJs. Reduced axon length, increased and shortened axon branches, MN action potential (AP) bursting and decreased AP firing rate and amplitude were observed in the NGLY1-deficient MNs in monoculture. When transitioned to the NMJ-coculture system, deficits in NMJ number, stability, failure rate, and synchronicity with indirect skeletal muscle (SkM) stimulation were observed. This project establishes a phenotypic NGLY1 model for investigation of possible therapeutics and investigations into mechanistic deficits in the system.

Seven years since the launch of the Matchmaker Exchange: The evolution of genomic matchmaking

The Matchmaker Exchange (MME) was launched in 2015 to provide a robust mechanism to discover novel disease-gene relationships. It operates as a federated network connecting databases holding relevant data using a common application programming interface, where two or more users are looking for a match for the same gene (two-sided matchmaking). Seven years from its launch, it is clear that the MME is making outstanding contributions to understanding the morbid anatomy of the genome. The number of unique genes present across the MME has steadily increased over time; there are currently >13,520 unique genes (~68% of all protein-coding genes) connected across the MME's eight genomic matchmaking nodes, GeneMatcher, DECIPHER, PhenomeCentral, MyGene2, seqr, Initiative on Rare and Undiagnosed Disease, PatientMatcher, and the RD-Connect Genome-Phenome Analysis Platform. The collective data set accessible across the MME currently includes more than 120,000 cases from over 12,000 contributors in 98 countries. The discovery of potential new disease-gene relationships is happening daily and international collaborative teams are moving these advances forward to publication, now numbering well over 500. Expansion of data sharing into routine clinical practice by clinicians, genetic counselors, and clinical laboratories has ensured access to discovery for even more individuals with undiagnosed rare genetic diseases. Tens of thousands of patients and their family members have been directly or indirectly impacted by the discoveries facilitated by two-sided genomic matchmaking. MME supports further connections to the literature (PubCaseFinder) and to human and model organism resources (Monarch Initiative) and scientists (ModelMatcher). Efforts are now underway to explore additional approaches to matchmaking at the gene or variant level where there is only one querier (one-sided matchmaking). Genomic matchmaking has proven its utility over the past 7 years and will continue to facilitate discoveries in the years to come.

Broadening Participation: 21st Century Opportunities for Amateurs in Biology Research

The modern field of biology has its roots in the curiosity and skill of amateur researchers and has never been purely the domain of professionals. Today, professionals and amateurs contribute to biology research, working both together and independently. Well-targeted and holistic investment in amateur biology research could bring a range of benefits that, in addition to positive societal benefits, may help to address the considerable challenges facing our planet in the 21st century. We highlight how recent advances in amateur biology have been facilitated by innovations in digital infrastructure as well as the development of community biology laboratories, launched over the last decade, and we provide recommendations for how individuals can support the integration of amateurs into biology research. The benefits of investment in amateur biology research could be many-fold, however without a clear consideration of equity, efforts to promote amateur biology could exacerbate structural inequalities around access to and benefits from STEM. The future of the field of biology relies on integrating a diversity of perspectives and approaches-amateur biology researchers have an important role to play.

Strategies to Uplift Novel Mendelian Gene Discovery for Improved Clinical Outcomes

Rare genetic disorders, while individually rare, are collectively common. They represent some of the most severe disorders affecting patients worldwide with significant morbidity and mortality. Over the last decade, advances in genomic methods have significantly uplifted diagnostic rates for patients and facilitated novel and targeted therapies. However, many patients with rare genetic disorders still remain undiagnosed as the genetic etiology of only a proportion of Mendelian conditions has been discovered to date. This article explores existing strategies to identify novel Mendelian genes and how these discoveries impact clinical care and therapeutics. We discuss the importance of data sharing, phenotype-driven approaches, patient-led approaches, utilization of large-scale genomic sequencing projects, constraint-based methods, integration of multi-omics data, and gene-to-patient methods. We further consider the health economic advantages of novel gene discovery and speculate on potential future methods for improved clinical outcomes.

Rare disease patient matchmaking: development and outcomes of an internet case-finding strategy in the Undiagnosed Diseases Network

BACKGROUND

Although clinician, researcher, and patient resources for matchmaking exist, finding similar patients remains an obstacle for rare disease diagnosis. The goals of this study were to develop and test the effectiveness of an Internet case-finding strategy and identify factors associated with increased matching within a rare disease population.

METHODS

Public web pages were created for consented participants. Matches made, time to each inquiry and match, and outcomes were recorded and analyzed using descriptive statistics. A Poisson regression model was run to identify characteristics associated with matches.

RESULTS

385 participants were referred to the project and 158 had pages posted. 579 inquiries were received; 89.0% were from the general public and 24.7% resulted in a match. 81.6% of pages received at least one inquiry and 15.0% had at least one patient match. Primary symptom category of neurology, diagnosis, gene page, and photo were associated with increased matches (p ≤ 0.05).

CONCLUSIONS

This Internet case-finding strategy was of interest to patients, families, and clinicians, and similar patients were identified using this approach. Extending matchmaking efforts to the general public resulted in matches and suggests including this population in matchmaking activities can improve identification of similar patients.

Landscape of Participant-Centric Initiatives for Medical Research in the United States, the United Kingdom, and Japan: Scoping Review

BACKGROUND

Information and communication technology (ICT) has made remarkable progress in recent years and is being increasingly applied to medical research. This technology has the potential to facilitate the active involvement of research participants. Digital platforms that enable participants to be involved in the research process are called participant-centric initiatives (PCIs). Several PCIs have been reported in the literature, but no scoping reviews have been carried out. Moreover, detailed methods and features to aid in developing a clear definition of PCIs have not been sufficiently elucidated to date.

OBJECTIVE

The objective of this scoping review is to describe the recent trends in, and features of, PCIs across the United States, the United Kingdom, and Japan.

METHODS

We applied a methodology suggested by Levac et al to conduct this scoping review. We searched electronic databases-MEDLINE (Medical Literature Analysis and Retrieval System Online), Embase (Excerpta Medica Database), CINAHL (Cumulative Index of Nursing and Allied Health Literature), PsycINFO, and Ichushi-Web-and sources of grey literature, as well as internet search engines-Google and Bing. We hand-searched through key journals and reference lists of the relevant articles. Medical research using ICT was eligible for inclusion if there was a description of the active involvement of the participants.

RESULTS

Ultimately, 21 PCIs were identified that have implemented practical methods and modes of various communication activities, such as patient forums and use of social media, in the field of medical research. Various methods of decision making that enable participants to become involved in setting the agenda were also evident.

CONCLUSIONS

This scoping review is the first study to analyze the detailed features of PCIs and how they are being implemented. By clarifying the modes and methods of various forms of communication and decision making with patients, this review contributes to a better understanding of patient-centric involvement, which can be facilitated by PCIs.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/resprot.7407.

Informed Consent in the Genomics Era

Informed consent, the process of gathering autonomous authorization for a medical intervention or medical research participation, is a fundamental component of medical practice. Medical informed consent assumes decision-making capacity, voluntariness, comprehension, and adequate information. The increasing use of genetic testing, particularly genomic sequencing, in clinical and research settings has presented many new challenges for clinicians and researchers when obtaining informed consent. Many of these challenges revolve around the need for patient comprehension of sufficient information. Genomic sequencing is complex-all of the possible results are too numerous to explain, and many of the risks and benefits remain unknown. Thus, historical standards of consent are difficult to apply. Alternative models of consent have been proposed to increase patient understanding, and several have empirically demonstrated effectiveness. However, there is still a striking lack of consensus in the genetics community about what constitutes informed consent in the context of genomic sequencing. Multiple approaches are needed to address this challenge, including consensus building around standards, targeted use of genetic counselors in nongenetics clinics in which genomic testing is ordered, and the development and testing of alternative models for obtaining informed consent.

Research data management in health and biomedical citizen science: practices and prospects

Background

Public engagement in health and biomedical research is being influenced by the paradigm of citizen science. However, conventional health and biomedical research relies on sophisticated research data management tools and methods. Considering these, what contribution can citizen science make in this field of research? How can it follow research protocols and produce reliable results?

Objective

The aim of this article is to analyze research data management practices in existing biomedical citizen science studies, so as to provide insights for members of the public and of the research community considering this approach to research.

Methods

A scoping review was conducted on this topic to determine data management characteristics of health and bio medical citizen science research. From this review and related web searching, we chose five online platforms and a specific research project associated with each, to understand their research data management approaches and enablers.

Results

Health and biomedical citizen science platforms and projects are diverse in terms of types of work with data and data management activities that in themselves may have scientific merit. However, consistent approaches in the use of research data management models or practices seem lacking, or at least are not prevalent in the review.

Conclusions

There is potential for important data collection and analysis activities to be opaque or irreproducible in health and biomedical citizen science initiatives without the implementation of a research data management model that is transparent and accessible to team members and to external audiences. This situation might be improved with participatory development of standards that can be applied to diverse projects and platforms, across the research data life cycle.

Genomic Data Sharing for Novel Mendelian Disease Gene Discovery: The Matchmaker Exchange

In the last decade, exome and/or genome sequencing has become a common test in the diagnosis of individuals with features of a rare Mendelian disorder. Despite its success, this test leaves the majority of tested individuals undiagnosed. This review describes the Matchmaker Exchange (MME), a federated network established to facilitate the solving of undiagnosed rare-disease cases through data sharing. MME supports genomic matchmaking, the act of connecting two or more parties looking for cases with similar phenotypes and variants in the same candidate genes. An application programming interface currently connects six matchmaker nodes-the Database of Chromosomal Imbalance and Phenotype in Humans Using Ensembl Resources (DECIPHER), GeneMatcher, PhenomeCentral, seqr, MyGene2, and the Initiative on Rare and Undiagnosed Diseases (IRUD) Exchange-resulting in a collective data set spanning more than 150,000 cases from more than 11,000 contributors in 88 countries. Here, we describe the successes and challenges of MME, its individual matchmaking nodes, plans for growing the network, and considerations for future directions.

The undiagnosed diseases program: Approach to diagnosis

Undiagnosed and rare conditions are collectively common and affect millions of people worldwide. The NIH Undiagnosed Diseases Program (UDP) strives to achieve both a comprehensive diagnosis and a better understanding of the mechanisms of disease for many of these individuals. Through the careful review of records, a well-orchestrated inpatient evaluation, genomic sequencing and testing, and with the use of emerging strategies such as matchmaking programs, the UDP succeeds nearly 30 percent of the time for these highly selective cases. Although the UDP process is built on a unique set of resources, case examples demonstrate steps genetic professionals can take, in both clinical and research settings, to arrive at a diagnosis for their most challenging cases.

Mendelian Gene Discovery: Fast and Furious with No End in Sight

Gene discovery for Mendelian conditions (MCs) offers a direct path to understanding genome function. Approaches based on next-generation sequencing applied at scale have dramatically accelerated gene discovery and transformed genetic medicine. Finding the genetic basis of ∼6,000-13,000 MCs yet to be delineated will require both technical and computational innovation, but will rely to a larger extent on meaningful data sharing.

Genomic variant sharing: a position statement

Sharing de-identified genetic variant data is essential for the practice of genomic medicine and is demonstrably beneficial to patients. Robust genetic diagnoses that inform medical management cannot be made accurately without reference to genetic test results from other patients, as well as population controls. Errors in this process can result in delayed, missed or erroneous diagnoses, leading to inappropriate or missed medical interventions for the patient and their family. The benefits of sharing individual genetic variants, and the harms of not sharing them, are numerous and well-established. Databases and mechanisms already exist to facilitate deposition and sharing of pseudonomised genetic variants, but clarity and transparency around best practice is needed to encourage widespread use, prevent inconsistencies between different communities, maximise individual privacy and ensure public trust. We therefore recommend that widespread sharing of a small number of individual genetic variants associated with limited clinical information should become standard practice in genomic medicine. Information robustly linking genetic variants with specific conditions is fundamental biological knowledge, not personal information, and therefore should not require consent to share. For additional case-level detail about individual patients or more extensive genomic information, which is often essential for clinical interpretation, it may be more appropriate to use a controlled-access model for data sharing, with the ultimate aim of making as much information as open and de-identified as possible with appropriate consent.

Genomic variant sharing: a position statement

Sharing de-identified genetic variant data is essential for the practice of genomic medicine and is demonstrably beneficial to patients. Robust genetic diagnoses that inform medical management cannot be made accurately without reference to genetic test results from other patients, as well as population controls. Errors in this process can result in delayed, missed or erroneous diagnoses, leading to inappropriate or missed medical interventions for the patient and their family. The benefits of sharing individual genetic variants, and the harms of not sharing them, are numerous and well-established. Databases and mechanisms already exist to facilitate deposition and sharing of pseudonomised genetic variants, but clarity and transparency around best practice is needed to encourage widespread use, prevent inconsistencies between different communities, maximise individual privacy and ensure public trust. We therefore recommend that widespread sharing of a small number of individual genetic variants associated with limited clinical information should become standard practice in genomic medicine. Information robustly linking genetic variants with specific conditions is fundamental biological knowledge, not personal information, and therefore should not require consent to share. For additional case-level detail about individual patients or more extensive genomic information, which is often essential for clinical interpretation, it may be more appropriate to use a controlled-access model for data sharing, with the ultimate aim of making as much information as open and de-identified as possible with appropriate consent.

Meeting Patients' Right to the Correct Diagnosis: Ongoing International Initiatives on Undiagnosed Rare Diseases and Ethical and Social Issues

The time required to reach a correct diagnosis is a key concern for rare disease (RD) patients. Diagnostic delay can be intolerably long, often described as an “odyssey” and, for some, a diagnosis may remain frustratingly elusive. The International Rare Disease Research Consortium proposed, as ultimate goal for 2017–2027, to enable all people with a suspected RD to be diagnosed within one year of presentation, if the disorder is known. Subsequently, unsolved cases would enter a globally coordinated diagnostic and research pipeline. In-depth analysis of the genotype through next generation sequencing, together with a standardized in-depth phenotype description and sophisticated high-throughput approaches, have been applied as diagnostic tools to increase the chance of a timely and accurate diagnosis. The success of this approach is evident in the Orphanet database. From 2010 to March 2017 over 600 new RDs and roughly 3600 linked genes have been described and identified. However, combination of -omics and phenotype data, as well as international sharing of this information, has raised ethical concerns. Values to be assessed include not only patient autonomy but also family implications, beneficence, non-maleficence, justice, solidarity and reciprocity, which must be respected and promoted and, at the same time, balanced among each other. In this work we suggest that, to maximize patients’ involvement in the search for a diagnosis and identification of new causative genes, undiagnosed patients should have the possibility to: (1) actively participate in the description of their phenotype; (2) choose the level of visibility of their profile in matchmaking databases; (3) express their preferences regarding return of new findings, in particular which level of Variant of Unknown Significance (VUS) significance should be considered relevant to them. The quality of the relationship between individual patients and physicians, and between the patient community and the scientific community, is critically important for optimizing the use of available data and enabling international collaboration in order to provide a diagnosis, and the attached support, to unsolved cases. The contribution of patients to collecting and coding data comprehensively is critical for efficient use of data downstream of data collection.

Incorporating Social Media into your Support Tool Box: Points to Consider from Genetics-Based Communities

Patients with newly-described or rare genetic findings are turning to social media to find and connect with others. Blogs, Facebook groups, and Twitter have all been reported as tools for patients to connect with one another. However, the preferences for social media use and privacy among patients, their families, and these communities have not been well characterized. To explore preferences about privacy and membership guidelines, an online survey was administered to two web-based patient registries, Simons Variation in Individuals Project ( www.simonsvipconnect.org ) and GenomeConnect ( www.genomeconnect.org ). Over a three-month period, invitations were sent to 2524 individuals and 103 responses (4%) were received and analyzed. Responses indicate that Facebook is the most popular resource accessed within this sample population (99%). Participants used social media to look for information about their diagnosis or test results (83%), read posts from rare disease groups or organizations (73%), participate in conversations about their diagnosis (67%), and connect with others to find support (58%). Focusing on privacy issues in social media, respondents indicate that membership and access impact the level of comfort in sharing personal or medical information. Nearly 60% of respondents felt uncomfortable sharing photos or medical information within a public Facebook group, whereas only 12% of respondents felt uncomfortable sharing in private group targeted to families alone. Using this preliminary data concerning social media use and privacy, we developed points for genetic counselors to incorporate when discussing available support resources for patients with a new, or rare, genetic diagnosis or genetic test result. Genetic counselors are trained to provide anticipatory guidance to families adapting to new genetic information, and are well-equipped to help patients consider their preferences about using social media as a source of information and support.

Participant-Partners in Genetic Research: An Exome Study with Families of Children with Unexplained Medical Conditions

BACKGROUND

Unlike aggregate research on groups of participants with a particular disorder, genomic research on discrete families' rare conditions could result in data of use to families, their healthcare, as well as generating knowledge on the human genome.

OBJECTIVE

In a study of families seeking to rule in/out genetic causes for their children's medical conditions via exome sequencing, we solicited their views on the importance of genomic information. Our aim was to learn the interests of parents in seeking genomic research data and to gauge their responsiveness and engagement with the research team.

METHODS

At enrollment, we offered participants options in the consent form for receiving potentially clinically relevant research results. We also offered an option of being a "partner" versus a "traditional" participant; partners could be re-contacted for research and study activities. We invited adult partners to complete a pre-exome survey, attend annual family forums, and participate in other inter-family interaction opportunities.

RESULTS

Of the 385 adults enrolled, 79% opted for "partnership" with the research team. Nearly all (99.2%) participants opted to receive research results pertaining to their children's primary conditions. A majority indicated the desire to receive additional clinically relevant outside the scope of their children's conditions (92.7%) and an interest in non-clinically relevant genetic information (82.7%).

CONCLUSIONS

Most participants chose partnership, including its rights and potential burdens; however, active engagement in study activities remained the exception. Not surprisingly, the overwhelming majority of participants-both partners and traditional-expected to receive all genetic information resulting from the research study.

International Cooperation to Enable the Diagnosis of All Rare Genetic Diseases

Provision of a molecularly confirmed diagnosis in a timely manner for children and adults with rare genetic diseases shortens their "diagnostic odyssey," improves disease management, and fosters genetic counseling with respect to recurrence risks while assuring reproductive choices. In a general clinical genetics setting, the current diagnostic rate is approximately 50%, but for those who do not receive a molecular diagnosis after the initial genetics evaluation, that rate is much lower. Diagnostic success for these more challenging affected individuals depends to a large extent on progress in the discovery of genes associated with, and mechanisms underlying, rare diseases. Thus, continued research is required for moving toward a more complete catalog of disease-related genes and variants. The International Rare Diseases Research Consortium (IRDiRC) was established in 2011 to bring together researchers and organizations invested in rare disease research to develop a means of achieving molecular diagnosis for all rare diseases. Here, we review the current and future bottlenecks to gene discovery and suggest strategies for enabling progress in this regard. Each successful discovery will define potential diagnostic, preventive, and therapeutic opportunities for the corresponding rare disease, enabling precision medicine for this patient population.

Evolving health care through personal genomics

With the rapid evolution of next-generation DNA sequencing technologies, the cost of sequencing a human genome has plummeted, and genomics has started to pervade health care across all stages of life - from preconception to adult medicine. Challenges to fully embracing genomics in a clinical setting remain, but some approaches are starting to overcome these barriers, such as community-driven data sharing to improve the accuracy and efficiency of applying genomics to patient care.

Novel bioinformatic developments for exome sequencing

With the widespread adoption of next generation sequencing technologies by the genetics community and the rapid decrease in costs per base, exome sequencing has become a standard within the repertoire of genetic experiments for both research and diagnostics. Although bioinformatics now offers standard solutions for the analysis of exome sequencing data, many challenges still remain; especially the increasing scale at which exome data are now being generated has given rise to novel challenges in how to efficiently store, analyze and interpret exome data of this magnitude. In this review we discuss some of the recent developments in bioinformatics for exome sequencing and the directions that this is taking us to. With these developments, exome sequencing is paving the way for the next big challenge, the application of whole genome sequencing.

Novel bioinformatic developments for exome sequencing

With the widespread adoption of next generation sequencing technologies by the genetics community and the rapid decrease in costs per base, exome sequencing has become a standard within the repertoire of genetic experiments for both research and diagnostics. Although bioinformatics now offers standard solutions for the analysis of exome sequencing data, many challenges still remain; especially the increasing scale at which exome data are now being generated has given rise to novel challenges in how to efficiently store, analyze and interpret exome data of this magnitude. In this review we discuss some of the recent developments in bioinformatics for exome sequencing and the directions that this is taking us to. With these developments, exome sequencing is paving the way for the next big challenge, the application of whole genome sequencing.

Not the End of the Odyssey: Parental Perceptions of Whole Exome Sequencing (WES) in Pediatric Undiagnosed Disorders

Due to the lack of empirical information on parental perceptions of primary results of whole exome sequencing (WES), we conducted a retrospective semi-structured interview with 19 parents of children who had undergone WES. Perceptions explored during the interview included factors that would contribute to parental empowerment such as: parental expectations, understanding of the WES and results, utilization of the WES information, and communication of findings to health/educational professionals and family members. Results of the WES had previously been communicated to families within a novel framework of clinical diagnostic categories: 5/19 had Definite diagnoses, 6/19 had Likely diagnoses, 3/19 had Possible diagnosis and 5/19 had No diagnosis. All parents interviewed expressed a sense of duty to pursue the WES in search of a diagnosis; however, their expectations were tempered by previous experiences with negative genetic testing results. Approximately half the parents worried that a primary diagnosis that would be lethal might be identified; however, the hope of a diagnosis outweighed this concern. Parents were accurately able to summarize their child's WES findings, understood the implications for recurrence risks, and were able to communicate these findings to family and medical/educational providers. The majority of those with a Definite/Likely diagnosis felt that their child's medical care was more focused, or there was a reduction in worry, despite the lack of a specific treatment. Irrespective of diagnostic outcome, parents recommended that follow-up visits be built into the process. Several parents expressed a desire to have all variants of unknown significance (VUS) reported to them so that they could investigate these themselves. Finally, for some families whose children had a Definite/Likely diagnosis, there was remaining frustration and a sense of isolation, due to the limited information that was available about the diagnosed rare disorders and the inability to connect to other families, suggesting that for families with rare genetic disorders, the diagnostic odyssey does not necessarily end with a diagnosis. Qualitative interviewing served a meaningful role in eliciting new information about parental motivations, expectations, and knowledge of WES. Our findings highlight a need for continued communication with families as we navigate the new landscape of genomic sequencing.

Gene discovery for Mendelian conditions via social networking: de novo variants in KDM1A cause developmental delay and distinctive facial features

PURPOSE

The pace of Mendelian gene discovery is slowed by the "n-of-1 problem"-the difficulty of establishing the causality of a putatively pathogenic variant in a single person or family. Identification of an unrelated person with an overlapping phenotype and suspected pathogenic variant in the same gene can overcome this barrier, but it is often impeded by lack of a convenient or widely available way to share data on candidate variants/genes among families, clinicians, and researchers.

METHODS

Social networking among families, clinicians, and researchers was used to identify three children with variants of unknown significance in KDM1A and similar phenotypes.

RESULTS

De novo variants in KDM1A underlie a new syndrome characterized by developmental delay and distinctive facial features.

CONCLUSION

Social networking is a potentially powerful strategy to discover genes for rare Mendelian conditions, particularly those with nonspecific phenotypic features. To facilitate the efforts of families to share phenotypic and genomic information with each other, clinicians, and researchers, we developed the Repository for Mendelian Genomics Family Portal (RMD-FP; http://uwcmg.org/#/family). Design and development of MyGene2 (http://www.mygene2.org), a Web-based tool that enables families, clinicians, and researchers to search for gene matches based on analysis of phenotype and exome data deposited into the RMD-FP, is under way.Genet Med 18 8, 788-795.

The Matchmaker Exchange: a platform for rare disease gene discovery

There are few better examples of the need for data sharing than in the rare disease community, where patients, physicians, and researchers must search for "the needle in a haystack" to uncover rare, novel causes of disease within the genome. Impeding the pace of discovery has been the existence of many small siloed datasets within individual research or clinical laboratory databases and/or disease-specific organizations, hoping for serendipitous occasions when two distant investigators happen to learn they have a rare phenotype in common and can "match" these cases to build evidence for causality. However, serendipity has never proven to be a reliable or scalable approach in science. As such, the Matchmaker Exchange (MME) was launched to provide a robust and systematic approach to rare disease gene discovery through the creation of a federated network connecting databases of genotypes and rare phenotypes using a common application programming interface (API). The core building blocks of the MME have been defined and assembled. Three MME services have now been connected through the API and are available for community use. Additional databases that support internal matching are anticipated to join the MME network as it continues to grow.

GenomeConnect: matchmaking between patients, clinical laboratories, and researchers to improve genomic knowledge

As the utility of genetic and genomic testing in healthcare grows, there is need for a high-quality genomic knowledge base to improve the clinical interpretation of genomic variants. Active patient engagement can enhance communication between clinicians, patients, and researchers, contributing to knowledge building. It also encourages data sharing by patients and increases the data available for clinicians to incorporate into individualized patient care, clinical laboratories to utilize in test interpretation, and investigators to use for research. GenomeConnect is a patient portal supported by the Clinical Genome Resource (ClinGen), providing an opportunity for patients to add to the knowledge base by securely sharing their health history and genetic test results. Data can be matched with queries from clinicians, laboratory personnel, and researchers to better interpret the results of genetic testing and build a foundation to support genomic medicine. Participation is online, allowing patients to contribute regardless of location. GenomeConnect supports longitudinal, detailed clinical phenotyping and robust "matching" among research and clinical communities. Phenotype data are gathered using online health questionnaires; genotype data are obtained from genetic test reports uploaded by participants and curated by staff. GenomeConnect empowers patients to actively participate in the improvement of genomic test interpretation and clinical utility.