Risk Assessment and Communication Tools for Genotype Associations with Multifactorial Phenotypes: The Concept of “Edge Effect” and Cultivating an Ethical Bridge between Omics Innovations and Society

Abstract

Applications of omics technologies in the postgenomics era swiftly expanded from rare monogenic disorders to multifactorial common complex diseases, pharmacogenomics, and personalized medicine. Already, there are signposts indicative of further omics technology investment in nutritional sciences (nutrigenomics), environmental health/ecology (ecogenomics), and agriculture (agrigenomics). Genotype-phenotype association studies are a centerpiece of translational research in omics science. Yet scientific and ethical standards and ways to assess and communicate risk information obtained from association studies have been neglected to date. This is a significant gap because association studies decisively influence which genetic loci become genetic tests in the clinic or products in the genetic test marketplace. A growing challenge concerns the interpretation of large overlap typically observed in distribution of quantitative traits in a genetic association study with a polygenic/multifactorial phenotype. To remedy the shortage of risk assessment and communication tools for association studies, this paper presents the concept of edge effect. That is, the shift in population edges of a multifactorial quantitative phenotype is a more sensitive measure (than population averages) to gauge the population level impact and by extension, policy significance of an omics marker. Empirical application of the edge effect concept is illustrated using an original analysis of warfarin pharmacogenomics and the VKORC1 genetic variation in a Brazilian population sample. These edge effect analyses are examined in relation to regulatory guidance development for association studies. We explain that omics science transcends the conventional laboratory bench space and includes a highly heterogeneous cast of stakeholders in society who have a plurality of interests that are often in conflict. Hence, communication of risk information in diagnostic medicine also demands attention to processes involved in production of knowledge and human values embedded in scientific practice, for example, why, how, by whom, and to what ends association studies are conducted, and standards are developed (or not). To ensure sustainability of omics innovations and forecast their trajectory, we need interventions to bridge the gap between omics laboratory and society. Appreciation of scholarship in history of omics science is one remedy to responsibly learn from the past to ensure a sustainable future in omics fields, both emerging (nutrigenomics, ecogenomics), and those that are more established (pharmacogenomics). Another measure to build public trust and sustainability of omics fields could be legislative initiatives to create a 43

Editorial (Nutriproteomics and Proteogenomics: Cultivating Two Novel Hybrid Fields of Personalized Medicine with Added Societal Value)

“…The recent call for a gene-centric HPP and the emerging field of proteogenomics already attest to the promise of such an alliance. Through upstream engagement from the outset, and together with real-time analyses of novel biotechnology applications, we can increase the likelihood of cultivating innovations with added societal value [7,8,12].…”

“…This project might also draw the genomics and proteomics communities much closer. Both communities share a complementary vision on data intensive 21 st century science [8,21,22] that aims to understand the human biology and the interacting environmental-societal factors at a systems level, for advances in diagnostic, preventive, prognostic and therapeutic end-points. Conceivably, the HPP will also stimulate spinoff novel proteomics platforms capable of higher throughput analyses, as with genomics technologies after the HGP, and thus drive down the cost of proteomics applications for personalized medicine in the future.…”

Translational Approaches In Cardiovascular Diseases by Omics

“…To achieve these goals, we need to dispose of comprehensive protein datasets in physiological and pathological conditions (Napoli et al, 2013) and to combine proteomics results with clinical phenotypes, metabolite changes and genetic haplotype information (Balestrieri, Giovane, Mancini and Napoli, 2008). This combination could also cover genotype-phenotype association (Ozdemir et al, 2009), which is an important aspect in the validation of a new biomarker and for phenotype prediction in population studies (Ritchie, Holzinger, Li, Pendergrass and Kim, 2015). The correlation between genotype and phenotype can prepare a guideline to develop treatment based on genetic testing (Goodsaid and Mattes, 2013).…”

Nutrigenomics 2.0: The Need for Ongoing and Independent Evaluation and Synthesis of Commercial Nutrigenomics Tests' Scientific Knowledge Base for Responsible Innovation

“…Indeed, emerging fields of technology and innovation are laden with contestation and thus, synthesis of evidence or the critique of evidence base (claims over presence or absence of it) should be considered with the intent, motivation, embedded values, conflict of interests, and sources of such critiques of science and innovation in a given field (De Vries, 2004;Petersen, 2013;Thoreau and Delvenne, 2012;van Oudheusden, 2014). A socio-technical history and emergence of nutrigenomics, and various omics systems science fields is available elsewhere (Ozdemir et al, 2009).…”