Population molecular genetics in Brazil: From genomic databases and research to the implementation of precision medicine

Journal of Community Genetics https://doi.org/10.1007/s12687-024-00752-5 REVIEW Population molecular genetics in Brazil: From genomic databases and research to the implementation of precision medicine Thais C. de Oliveira1,2 · Iscia Lopes‑Cendes1,2 Received: 18 July 2024 / Accepted: 5 November 2024 © The Author(s) 2024 Abstract Precision medicine (PM) stands on the brink of revolutionizing medical practice throughout the world, holding significant potential for enhancing patient outcomes. However, its practical implementation, particularly in resource-limited countries, is not without challenges. The success of PM largely hinges on the availability of extensive datasets, including genetic and genomic information. This paper delves into the PM landscape and the current state of genetic and genomic testing in Brazil. We also shed light on the unique challenges posed by the country’s diverse population and discuss ongoing initiatives to tackle these obstacles. Keywords Population genomics · Genomic medicine · Genetic testing · Genomics in Latin America Background Precision medicine (PM), an approach to healthcare that aims to shape medical care to individual characteristics, is set to revolutionize medical practice worldwide. By integrating genomics, transcriptomics, proteomics, and other types of omics information with multidimensional clinical and exposure data, PM aims to provide personalized diagnoses and therapies with improved efficacy and fewer adverse effects (Martschenko and Young 2022). While this paradigm shift holds immense promise for improving patient outcomes, its practical implementation faces various challenges, particularly in regions with limited resources. In addition, one of the fundamental principles of PM is to consider individual genetic information, among many other characteristics, when diagnosing and defining treatment. Thus, as PM is incorporated fully into medical practice, obtaining a partial or complete sequence of a patient’s genome * Iscia Lopes‑Cendes 1 Department of Medical Genetics and Genomic Medicine, School of Medical Sciences, University of Campinas – UNICAMP, Tessália Vieira de Camargo, 126. Cidade Universitária “Zeferino Vaz”, Campinas, SP 13083‑888, Brazil 2 The Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), Campinas, Brazil will be an integral part of routine medical assessment. One expects genetic testing—involving the search for isolated mutations or the use of disease-specific mutation panels—or genomic testing—used here to denote genetic testing performed by sequencing large portions of the genome or the entire genome—to become a routine assessment in clinical practice, including in complex disorders with polygenic mechanisms and /or multifactorial causes. However, PM is not quite at this place yet. It is still limited to using genetic testing only for monogenic disorders. Nonetheless, the past decade has seen a marked change in our ability to employ genetic/genomic testing in clinical practice due to the many advances in sequencing technologies and our better understanding of the relationship between genetic variations and disease, reassuring us of the progress that has been made in PM. Population structure and disease susceptibility PM involves more than exploring massive sequencing as a solution. It is a multifaceted approach that integrates several types of data—clinical, environmental, genetic, and omics—into medical decision-making. So, the aim is not just to sequence a huge number of individuals of each population, but also to develop a robust understanding of genetic diversity and disease susceptibility within different contexts. Vol.:(0123456789) Journal of Community Genetics We recognize that individual genetic/genomic information interacts with adaptive evolution, ancestry, demography, history, and socioeconomic and environmental factors that may, in turn, influence disease susceptibility and treatment response in a much broader way than only determined by straightforward biology (Wright et al. 2019). While population admixture introduces valuable genetic diversity, obtaining representative and valid results requires one to consider more than just a mixture of different ancestral populations. Adequately stratified sampling based on metadata variables is also crucial to minimize biases from hidden subpopulations and to ensure that results are clinically relevant and actionable (Hindorff et al. 2018; Landry et al. 2018). In this way, we are just beginning to investigate if and how admixture may impact disease susceptibility, given that admixed populations have been absent from most large-scale genomic studies devoted to unraveling the genetic architecture of complex disorders (Arboleda-Velasquez et al. 2019). Thus, for most complex disorders, the extent to which disease susceptibility is influenced by common variants shared across populations or rare variants specific to certain populations is still unknown. In addition, the level to which variants can penetrate a population might differ depending on their genetic or environmental context (Wright et al. 2019; Fahed et al. 2020) and can be influenced by rare variants (Cooper et al. 2013) or a polygenic profile (Bitarello and Mathieson 2020). This phenomenon has been well documented in monogenic disorders presenting clinical variability in distinct families (Zhu and Cooper 2007), as well as the observations that population-specific genomic architecture modifies the distribution of polygenic risk scores (Bitarello and Mathieson 2020) and diminishes genome-wide association study (GWAS) replication (Marigorta and Navarro 2013). These findings suggest that studying recently admixed populations may disclose population-specific relationships relevant to better understanding complex disorders. However, most genomics studies have focused on populations of European descent, which has led to a significant underrepresentation of specific populations (Sirugo et al. 2019). This lack of diversity leads to a direct loss in the applicability of the most recent genomic findings to African, Native, and mixed ancestry populations in Latin America and the Caribbean (LAC). Furthermore, there is an indication that disease susceptibility among admixed populations may be genetically determined, as there is suggestive evidence of an association between the proportion of local ancestry (inherited from a given source) and disease susceptibility (Manolio et al. 2008). Admixed individuals could also contribute disproportionately to the significant findings of a GWAS compared with European or Asian populations, a phenomenon that is consistent with a higher genetic diversity, mainly found in African populations (Gurdasani et al. 2015). This effect can also be observed in African descendants of Europeancolonized countries outside the African continent. Furthermore, ancestry/population-specific single nucleotide variants (SNPs) and copy number variations (CNVs) have (...truncated)