Alexandre C. Pereira

International audience

While South Americans are underrepresented in human genomic diversity studies, Brazil has been a classical model for population genetics studies on admixture. We present the results of the EPIGEN Brazil Initiative, the most comprehensive up-to-date genomic analysis of any Latin-American population. A population-based genome-wide analysis of 6,487 individuals was performed in the context of worldwide genomic diversity to elucidate how ancestry, kinship, and inbreeding interact in three populations with different histories from the Northeast (African ancestry: 50%), Southeast, and South (both with European ancestry >70%) of Brazil. We showed that ancestry-positive assortative mating permeated Brazilian history. We traced European ancestry in the Southeast/South to a wider European/Middle Eastern region with respect to the Northeast, where ancestry seems restricted to Iberia. By developing an approximate Bayesian computation framework, we infer more recent European immigration to the Southeast/South than to the Northeast. Also, the observed low Native-American ancestry (6-8%) was mostly introduced in different regions of Brazil soon after the European Conquest. We broadened our understanding of the African diaspora, the major destination of which was Brazil, by revealing that Brazilians display two within-Africa ancestry components: one associated with non-Bantu/western Africans (more evident in the Northeast and African Americans) and one associated with Bantu/eastern Africans (more present in the Southeast/South). Furthermore, the whole-genome analysis of 30 individuals (42-fold deep coverage) shows that continental admixture rather than local post-Columbian history is the main and complex determinant of the individual amount of deleterious genotypes.

Brazil never had segregation laws defining membership of an ethnoracial group. Thus, the composition of the Brazilian population is mixed, and its ethnoracial classification is complex. Previous studies showed conflicting results on the correlation between genome ancestry and ethnoracial classification in Brazilians. We used 370,539 Single Nucleotide Polymorphisms to quantify this correlation in 5,851 community-dwelling individuals in the South (Pelotas), Southeast (Bambui) and Northeast (Salvador) Brazil. European ancestry was predominant in Pelotas and Bambui (median = 85.3% and 83.8%, respectively). African ancestry was highest in Salvador (median = 50.5%). The strength of the association between the phenotype and median proportion of African ancestry varied largely across populations, with pseudo R(2) values of 0.50 in Pelotas, 0.22 in Bambui and 0.13 in Salvador. The continuous proportion of African genomic ancestry showed a significant S-shape positive association with self-reported Blacks in the three sites, and the reverse trend was found for self reported Whites, with most consistent classifications in the extremes of the high and low proportion of African ancestry. In self-classified Mixed individuals, the predicted probability of having African ancestry was bell-shaped. Our results support the view that ethnoracial self-classification is affected by both genome ancestry and non-biological factors.

High-throughput metabolomics investigations, when conducted in large human cohorts, represent a potentially powerful tool for elucidating the biochemical diversity underlying human health and disease. Large-scale metabolomics data sources, generated using either targeted or nontargeted platforms, are becoming more common. Appropriate statistical analysis of these complex high-dimensional data will be critical for extracting meaningful results from such large-scale human metabolomics studies. Therefore, we consider the statistical analytical approaches that have been employed in prior human metabolomics studies. Based on the lessons learned and collective experience to date in the field, we offer a step-by-step framework for pursuing statistical analyses of cohort-based human metabolomics data, with a focus on feature selection. We discuss the range of options and approaches that may be employed at each stage of data management, analysis, and interpretation and offer guidance on the analytical decisions that need to be considered over the course of implementing a data analysis workflow. Certain pervasive analytical challenges facing the field warrant ongoing focused research. Addressing these challenges, particularly those related to analyzing human metabolomics data, will allow for more standardization of as well as advances in how research in the field is practiced. In turn, such major analytical advances will lead to substantial improvements in the overall contributions of human metabolomics investigations.

BACKGROUND: The impact of increased central arterial stiffness as a predictor of morbidity and mortality, independently of other cardiovascular (CV) risk factors, has been established. The main aim of the present work was to investigate the association of ethnicity on arterial stiffness in different ethnic groups from the Brazilian population. METHODS: A total of 1,427 individuals from the general population were randomly selected from the Vitoria City metropolitan area and 588 Amerindians from a native community in Brazil. The ethnicity of the general population was classified by a standard questionnaire as Caucasian descent, African descent, or Mulattos (considered racially mixed subjects). Pulse wave velocity (PWV) was measured with a noninvasive automatic device (Complior, Colson; Garges les Gonesses, France). RESULTS: Hemodynamic data of PWV, systolic blood pressure (SBP), diastolic blood pressure (DBP), and mean blood pressure (MBP) was higher in African descent individuals than in the other groups (P < 0.001). These results were still observed after adjustment for age and mean arterial pressure (P < 0.001). In addition, studying only normotensive individuals, PWV adjusted levels were higher in African descent individuals, and lower in Amerindians when compared with other ethnic groups (P < 0.01), showing, without the possible confounder effects of time and severity of hypertension or medication use, that PWV is associated with ethnicity in our population. CONCLUSION: The study of different ethnic groups from a highly admixtured population was able to demonstrate an association between ethnicity and arterial stiffness.