Janis Geary

Including underrepresented population groups in databases and initiatives integral to assessing hereditary cancer risk presents several challenges. Data and knowledge from genome-wide association studies (GWASs) and clinical genomics are based largely on people with predominantly European ancestry. Individuals who do not have this ancestry are under-represented in resources used to make clinical assessments. They are therefore more likely to receive results of “variant of unknown significance” (VUS) from genetic testing. Efforts to broaden representation of population groups have created additional challenges in grouping those with mixed ancestry. Further, the focus on genetics can lead to downplaying the impacts of racism. We describe challenges that must be overcome to include underrepresented population groups, including our insights from our ongoing work within each of 3 population groups that focus on: health care access for heterogeneous Hispanic/Latino populations, engagement with Black, African, and African Diasporic communities, and Indigenous Data sovereignty. Using empirical data derived from population databases, we demonstrate gaps in hereditary cancer gene variant representation. Our interviews with experts in genetic testing and data sharing suggest ways to create inclusive hereditary cancer data resources. The interview data highlight the inequities that have led to underrepresentation, ranging from patient access to research and health services (especially those that are culturally-sensitive), to funding available for professional training and grants to those who belong to underrepresented groups. Our goal is to ensure the realities of how different excluded groups experience genetic testing are not overlooked in the development of policy to address the broad challenge of hereditary cancer gene variant data sharing. There is no one simple solution to making more inclusive hereditary cancer data resources, but there are many opportunities to improve them and better serve these populations.

Genetic testing for inherited cancer risk changed dramatically when the US Supreme Court handed down unanimous rulings in Mayo v. Prometheus (2012) and Myriad v. Association for Molecular Pathology (2013). Those decisions struck down claims to methods based on ‘laws of nature’ (Mayo) and DNA molecules corresponding to sequences found in nature (Myriad). Senators Thom Tillis (R-NC) and Christopher Coons (D-DE) introduced legislation that would abrogate those decisions and specify narrow statutory exclusions to patent-eligibility in §101 of the US Patent Act. What would be the consequences of doing so? The Supreme Court decisions coincided with changes in how genetic tests were performed, reimbursed and regulated. Multi-gene sequencing supplanted oligo-gene testing as the cost of sequencing dropped 10,000-fold. Payers dramatically changed reimbursement practices. Food and Drug Administration regulation was proposed and remains in prospect. Databases for clinical interpretation made data freely available, augmenting a knowledge commons. The spectacular implosion of Theranos tempered investment in molecular diagnostics. These factors all complicate explanations of why venture capital funding for molecular diagnostics dropped relative to other sectors. Restoring patent-eligibility would put renewed pressure on other patent doctrines, such as obviousness, enablement and written description, that were not raised in the Supreme Court cases.

Sharing cancer gene variant and relevant clinical data could accelerate progress in cancer genomics. However, data sharing is currently impeded by issues related to financial sustainability, equity, incentives, privacy and security, and data quality. Evidence-based policy options to facilitate data sharing in these domains, and ultimately improve interpretation of cancer-associated genomic variants, are therefore needed. We conducted a modified policy Delphi with expert stakeholders that involved generating, evaluating, and ranking potential policy options to address these issues, with a focus on the US context. We found policy options in the financial sustainability domain were highly ranked, particularly stable funding for trusted entities. However, some Delphi panelists noted that the culture of public research funding has favored short-term grants. Panelists favored policy options focused on action by funders, which had the highest overall total scores that combined effectiveness and feasibility ratings and priority ranking within domains. Panelists also endorsed some policy options connected to actors such as journals, but they were more skeptical of policy options connected to legislative actors and data resources. These findings are critical inputs for policy makers as they consider policies to enable sharing of cancer gene variant data to improve health.

Germline genetic testing for inherited cancer risk has shifted to multi-gene panel tests (MGPTs). While MGPTs detect more pathogenic variants, they also detect more variants of uncertain significance (VUSs) that increase the possibility of harms such as unnecessary surgery. Data sharing by laboratories is critical to addressing the VUS problem. However, barriers to sharing and an absence of incentives have limited laboratory contributions to the ClinVar database. Payers can play a crucial role in the expansion of knowledge and effectiveness of genetic testing. Current policies affecting MGPT reimbursement are complex and create perverse incentives. Trends in utilization and coverage for private payers and Medicare illustrate opportunities and challenges for data sharing to close knowledge gaps and improve clinical utility. Policy options include making data sharing (i) a condition of payment, and (ii) a metric of laboratory quality in payment contracts, yielding preferred coverage or enhanced reimbursement. Mandating data sharing sufficient to verify interpretations and resolve discordance among labs under Medicare and federal health programs is an option for the US Congress. Such policies can reduce the current waste of valuable data needed for precision oncology and improved patient outcomes, enabling a learning health system.

The aim to sequence, catalog, and characterize the genomes of all of Earth’s eukaryotic biodiversity is the shared mission of many ongoing large-scale biodiversity genomics initiatives. Reference genomes of global flora and fauna have the potential to inform a broad range of major issues facing both biodiversity and humanity, such as the impact of climate change, the conservation of endangered species and ecosystems, public health crises, and the preservation and enhancement of ecosystem services. Biodiversity is dramatically declining: 28% of species being assessed by the IUCN are threatened with extinction, and recent reports suggest that a transformative change is needed to conserve and protect what remains. To provide a collective and global genomic response to the biodiversity crisis, many biodiversity genomics initiatives have come together, creating a network of networks under the Earth BioGenome Project. This network seeks to expedite the creation of an openly available, “public good” encyclopedia of high-quality eukaryotic reference genomes, in the hope that by advancing our basic understanding of nature, it can lead to the transformational scientific developments needed to conserve and protect global biodiversity. Key to completing this ambitious encyclopedia of reference genomes, is the ability to responsibly, ethically, legally, and equitably access and use samples from all of the eukaryotic species across the planet, including those that are under the custodianship of Indigenous Peoples and Local Communities. Here, the biodiversity genomics community is subject to the provisions codified in international, national, and local legislations and customary community norms, principles, and protocols. We propose a framework to support biodiversity genomic researchers, projects, and initiatives in building trustworthy and sustainable partnerships with communities, providing minimum recommendations on how to access, utilize, preserve, handle, share, analyze, and communicate samples, genomics data, and associated Traditional Knowledge obtained from, and in partnership with, Indigenous Peoples and Local Communities across the data-lifecycle.

Background: Children attending child care are vulnerable to SARS CoV-2 infection, and mitigationmeasures like masking, distancing, enhanced hygiene are not feasible for this population. Describingoutbreak growth during the COVID-19 pandemic in child care centres may provide insight in how to bestmitigate the risks of COVID-19 and other infectious diseases in these settings.Objective: To describe the characteristics of child care outbreaks and associated cases in Alberta.Methods: Our observational study used data on outbreaks and associated cases tracked through theAlberta Health Services Communicable Disease Outbreak Management database. We included allCOVID-19 outbreaks opened in child care facilities in the province (March 2020 to December 31, 2021).We compared the characteristics of outbreaks and cases during each wave of the pandemic.Outcome: 841 outbreaks were opened in Alberta, including 4613 cases (70.2% in children and 29.8%adults). Outbreaks averaged 5.5 cases per outbreak, and the average duration of time betweensymptoms starting in the first and last case was 9.7 days. The likely index was a child in 55.1% ofoutbreaks.Conclusions: Adults are a high proportion of cases compared to their proportion of the population atchild care facilities, and have consistently higher attack rates than children. Children have the highestattack rates when other children are the index case. Measures shown to be effective in other settings toreduce spread among adults can be implemented here, such as vaccination, strictly enforcing exclusionof those symptomatic, and facilitating rapid testing.

Hereditary cancer syndromes occur when germline variants increase an individual’s risk of developing cancer. Genetic testing can identify these variants, enabling clinicians to intervene through increased screening or prophylactic surgery. Advances in DNA sequencing have driven a shift to sequence-based testing of multiple genes and to subsequent classification of the identified variants. This approach has generated copious data, but a serious problem remains: New variants in cancer genes are discovered daily that cannot be classified (scientifically or clinically). This problem of variants of unknown significance (VUSs) is exacerbated in groups with predominantly non-European ancestry who have not been included in data sets used to interpret variants because of underrepresentation in genetic studies and diminished access to clinical genetic testing.¹ Fewer data lead to a higher proportion of VUSs.² Policies for data sharing and the related infrastructure are emerging to support variant classifications.³ To inform these efforts, we have compiled a list of genes included in hereditary cancer genetic testing panels. We also describe publicly available variant data for those genes. Our analysis identifies substantial variability across panels and gaps in available variant data that should be a focus for those engaged in building a robust system for interpreting inherited cancer risk.

Understanding the clinical significance of variants associated with hereditary cancer risk requires access to a pooled data resource or network of resources—a “cancer gene variant commons”—incorporating representative, well-characterized genetic data, metadata, and, for some purposes, pathways to case-level data. Several initiatives have invested significant resources into collecting and sharing cancer gene variant data, but further progress hinges on identifying and addressing unresolved policy issues. This commentary provides insights from a modified policy Delphi process involving experts from a range of stakeholder groups involved in the data-sharing ecosystem. In particular, we describe policy issues and options generated by Delphi participants in five domains critical to the development of an effective cancer gene variant commons: incentives, financial sustainability, privacy and security, equity, and data quality. Our intention is to stimulate wider discussion and lay a foundation for further work evaluating policy options more in-depth and mapping them to those who have the power to bring about change. Addressing issues in these five domains will contribute to a cancer gene variant commons that supports better care for at-risk and affected patients, empowers patient communities, and advances research on hereditary cancers.

In “Obligations of the ‘Gift’: Reciprocity and Responsibility in Precision Medicine,” Lee (2021) rightly points out that disparities in health care access also lead to disparities in precision medi...