The Need for Inclusive Genomic Research

HomeCirculation: Genomic and Precision MedicineVol. 15, No. 2The Need for Inclusive Genomic Research Free AccessEditorialPDF/EPUBAboutView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toFree AccessEditorialPDF/EPUBThe Need for Inclusive Genomic Research Neesha Krishnan and Jodie Ingles Neesha KrishnanNeesha Krishnan Centre for Population Genomics, Garvan Institute of Medical Research, Darlinghurst, Australia (N.K., J.I.). UNSW Sydney, Australia (N.K., J.I.). Centre for Population Genomics, Murdoch Children’s Research Institute, Melbourne, Australia (N.K., J.I.). Search for more papers by this author and Jodie InglesJodie Ingles Correspondence to: Jodie Ingles, PhD, MPH, Clinical Genomics Laboratory, Centre for Population Genomics, Garvan Institute of Medical Research, 384 Victoria St, Darlinghurst NSW 2010, Australia. Email E-mail Address: [email protected] https://orcid.org/0000-0002-4846-7676 Centre for Population Genomics, Garvan Institute of Medical Research, Darlinghurst, Australia (N.K., J.I.). UNSW Sydney, Australia (N.K., J.I.). Centre for Population Genomics, Murdoch Children’s Research Institute, Melbourne, Australia (N.K., J.I.). Department of Cardiology, Royal Prince Alfred Hospital, Sydney, Australia (J.I.). Search for more papers by this author Originally published21 Mar 2022https://doi.org/10.1161/CIRCGEN.122.003736Circulation: Genomic and Precision Medicine. 2022;15This article is a commentary on the followingCausative Variants for Inherited Cardiac Conditions in a Southeast Asian Population CohortOther version(s) of this articleYou are viewing the most recent version of this article. Previous versions: March 21, 2022: Ahead of Print Inherited cardiac conditions are heterogeneous diseases that often affect young people and can have potential for considerable morbidity and mortality. Cardiac genetic testing plays an essential role in management of families, being a powerful tool for clarifying risk for relatives. Increasingly, there are opportunities for genotype to guide management decisions, and these are beginning to be integrated into clinical guideline recommendations.1 After decades of research contributions, the collective diagnostic yield of genetic testing for these conditions remains at ≈40%.2 Ascertaining the underlying genetic basis among those who do not have a causative variant identified is a focus of current research, with growing recognition of a polygenic contribution in a proportion3 and intense gene discovery efforts targeted at families with suspected monogenic disease.4 Achieving a genetic diagnosis can clarify the cause of disease, inform management in some, and create options for the family to better understand their risk and need for ongoing surveillance. Indeed, the addition of genetic testing is cost-effective compared with clinical screening alone.5 Despite these clear benefits, our ability to provide a genetic diagnosis for families is not equal across the population. For individuals from diverse ancestry groups, it is even more difficult to interpret evidence for variant pathogenicity, leading to a greater likelihood of receiving an uncertain genetic result. In a rapidly evolving field where genomic medicine is increasingly able to add value to clinical care, the utility of genetic testing in people of diverse and underrepresented ancestries requires urgent attention to prevent a widening of health inequities.See Article by Tomar et alIn this issue, Tomar et al describe the presence of variants associated with inherited cardiac conditions in an impressive population-based cohort of 4810 healthy Singaporeans. The SG10K pilot database of South East Asian Genomes includes Chinese (n=2780), Malay (n=903), and Indian (n=1127) participants.6 Following careful variant interpretation and after 2 levels of review, 55 likely pathogenic/pathogenic variants were identified, present in 89 individuals (1.85%). Critically, several variants previously considered causative of an inherited cardiac condition underwent a downgrade in classification due to a minor allele frequency that was too high in the SG10K cohort, illustrating the power of such data in clarifying our interpretation of variants in patient populations. The authors highlight the current challenges in determining actionability of secondary genetic findings in a population lacking ancestry-matched reference data and demonstrate the critical limitations and risk of variant misclassification.Rarity of a Variant in General Population Data Sets Empowers Variant InterpretationThe likelihood that a variant is the cause of a rare monogenic disease can be guided, in part, by its frequency in cases with concordant phenotypes and in apparently healthy control populations. With increasingly large population reference databases, for example, the Genome Aggregation Database v2.1 includes 125 748 exomes and 15 708 genomes,7 there is greater resolution of the true frequency of variants in the population. While currently available reference databases allow us to filter out countless variants that occur more frequently than would be expected based on disease prevalence, penetrance, and genetic heterogeneity,8 with limited diversity of included participants, there is still a long way to go in using the rarity of a variant to empower variant curation efforts. Further, there remains the risk that we fail to identify a common variant by having not sampled the appropriate population.THE NEED for Inclusive Genomic Reference DatabasesIn large part due to a lack of ancestry-matched population reference data, individuals from diverse ancestry groups are less likely to receive an informative genetic result, that is, where a pathogenic or likely pathogenic variant is identified as the cause of disease.9–11 As such, interpretation of variants becomes fundamentally challenging, resulting in a larger burden of variants of uncertain significance. In the study by Tomar et al, 2 variants previously classified as pathogenic were identified in the SG10K cohort: MYBPC3 p.Glu334Lys was observed in 13 of 4810 (0.03%) and SCN5A p.Asp1819Asn was observed in 13 of 4810 (0.03%). While both variants currently have conflicting interpretations in ClinVar, ancestry-matched reference data have clarified the true frequency of the variant in a broader cross section of the population.Uncertain genetic results are not only more problematic for the family to adequately comprehend but can lead to a greater risk of misclassification.11 The potential harm caused by a misclassified variant cannot be underestimated. A variant may be incorrectly considered causative (false positive) due to apparent overrepresentation in cases and absence in nonmatched population data. A false positive result can elicit changes in management, treatment, and lifestyle modifications for the index case. For the family, inappropriate testing for the presence or absence of the variant via cascade genetic testing, to guide who continues to undergo periodic clinical surveillance and who can be released from future clinical testing and worry, is of the greatest concern.12 Reclassification is an inherent risk in genetic testing, where our understanding of how genetic variants lead to disease is rapidly evolving; however, in recent years, far more stringent approaches to variant classification and wider sharing of data aim to minimize the number of clinically meaningful variant reclassifications. Reclassification of variants can seed distrust in clinical care and research, and this can in turn affect research participation.13 With knowledge that people of diverse ancestry backgrounds including those of Asian descent may be less likely to participate in research in the first place due to a lack of trust and the presence of language barriers, the cyclical nature of how barriers to participation can be reinforced are highlighted.14Lack of Diversity in ResearchThe large majority of the research cohorts used to inform clinical management of patients with inherited cardiac diseases are of European descent. For example, the large collaborative Sarcomere Human Cardiomyopathy Registry includes ≈85% of participants with European ancestry.15 It is well described that patients of European ancestry are overrepresented in clinical research, with many more studies failing to even report the breakdown of participants by ancestry, racial group, or ethnicity.16 As the basis for guideline recommendations and clinical decision-making, ensuring research cohorts are representative of the patients they serve is a clear priority. For patients with inherited cardiac conditions, more inclusive research cohorts would allow better estimation of penetrance of genetic variants. Tomar et al highlight that the identification of likely pathogenic/pathogenic variants in LPL and LDLR in the SG10K cohort could suggest subclinical or reduced penetrance of familial hyperlipidemia in the population. Such a finding would have important implications in ascertaining risk in this population but also more broadly. More focused efforts to recruit diverse patients into research could unveil nuances in penetrance, genetic architecture, and clinical presentation that benefit our entire population.Likewise, genome-wide association studies (GWAS) can provide better understanding of genetic architecture and lead to the discovery of novel biological mechanisms. With increasing recognition of polygenic contributions to inherited cardiac conditions, diversity in GWAS is important to consider. Among the GWAS literature as a whole, European individuals have accounted for ≈92% of participants in studies,17 and ≈72% have been recruited from the United States, the United Kingdom, and Iceland.18 Historical methodological approaches limiting GWAS analyses to European patients only, the opportunistic recruitment of individuals easy to engage in research, and the long-held view that it would be acceptable to start with European populations initially and then add other populations over time19 have all limited diversity of participants and utility of polygenic risk score across the population. More inclusive research cohorts for GWAS development, refinement, and clinical utility will ensure health disparities are not further increased.Achieving DiversityAchieving diversity in research requires us to develop cultural responsiveness among our research teams, allowing us to engage with diverse communities to cultivate and build trust. Codesign is a participatory method that allows research participants to work together with researchers to better understand the research question and how it can be addressed. Use of codesign among underrepresented populations to increase engagement and participation could be of great value in certain contexts, though given the cultural diversity that may exist between ancestry groups, this will require deep engagement with individual communities to be most useful.20 Developing a greater appreciation among researchers, clinicians, funding bodies, policymakers and other key stakeholders of the social, ethical, and scientific imperative for inclusive research is needed. Further, intentional effort to create diverse research teams is essential for building an internal comprehension of the effects of systemic and institutionalized racism. To enable a broader and more inclusive vision of how research can inform and guide better outcomes for patients, more perspective is required from within. The intentionality that results from fostering a diverse workplace will translate into positive research impacts.21ConclusionAt an individual level, genetic testing for inherited cardiac conditions can enhance risk stratification, improve family management, refine diagnostic accuracy, and most importantly, empower patients to make educated decisions for their own health. In the contemporary setting, as researchers and clinicians, we should be aware of the limitations posed by this historical focus on European populations and consider how we can enable more inclusive and equitable outcomes. There is both a moral and scientific need to find ways to achieve more diversity in our research if we are to ensure that new discoveries and a move toward precision medicine approaches to care become a reality for our entire population, regardless of their ancestry.Article InformationAcknowledgmentsDr Ingles is the recipient of an National Heath and Medical Research Council Career Development Fellowship (No. 1162929).Disclosures None.FootnotesThe opinions expressed in this article are not necessarily those of the editors or of the American Heart Association.For Disclosures, see page 112.Correspondence to: Jodie Ingles, PhD, MPH, Clinical Genomics Laboratory, Centre for Population Genomics, Garvan Institute of Medical Research, 384 Victoria St, Darlinghurst NSW 2010, Australia. Email jodie.[email protected].org.auReferences1. 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