Significance: The EPIGEN Brazil Project is the largest Latin-American initiative to study the genomic diversity of admixed populations and its effect on phenotypes. We studied 6,487 Brazilians from three population-based cohorts with different geographic and demographic backgrounds. We identified ancestry components of these populations at a previously unmatched geographic resolution. We broadened our understanding of the African diaspora, the principal destination of which was Brazil, by revealing an African ancestry component that likely derives from the slave trade from Bantu/eastern African populations. In the context of the current debate about how the pattern of deleterious mutations varies between Africans and Europeans, we use whole-genome data to show that continental admixture is the main and complex determinant of the amount of deleterious genotypes in admixed individuals.

The Transatlantic Slave Trade transported more than 9 million Africans to the Americas between the early 16th and the mid-19th centuries. We performed a genome-wide analysis using 6,267 individuals from 25 populations to infer how different African groups contributed to North-, South-American, and Caribbean populations, in the context of geographic and geopolitical factors, and compared genetic data with demographic history records of the Transatlantic Slave Trade. We observed that West-Central Africa and Western Africa-associated ancestry clusters are more prevalent in northern latitudes of the Americas, whereas the South/East Africa-associated ancestry cluster is more prevalent in southern latitudes of the Americas. This pattern results from geographic and geopolitical factors leading to population differentiation. However, there is a substantial decrease in the between-population differentiation of the African gene pool within the Americas, when compared with the regions of origin from Africa, underscoring the importance of historical factors favoring admixture between individuals with different African origins in the New World. This between-population homogenization in the Americas is consistent with the excess of West-Central Africa ancestry (the most prevalent in the Americas) in the United States and Southeast-Brazil, with respect to historical-demography expectations. We also inferred that in most of the Americas, intercontinental admixture intensification occurred between 1750 and 1850, which correlates strongly with the peak of arrivals from Africa. This study contributes with a population genetics perspective to the ongoing social, cultural, and political debate regarding ancestry, admixture, and the mestizaje process in the Americas.

Western South America was one of the worldwide cradles of civilization. The well-known Inca Empire was the tip of the iceberg of an evolutionary process that started 11,000 to 14,000 years ago. Genetic data from 18 Peruvian populations reveal the following: 1) The between-population homogenization of the central southern Andes and its differentiation with respect to Amazonian populations of similar latitudes do not extend northward. Instead, longitudinal gene flow between the northern coast of Peru, Andes, and Amazonia accompanied cultural and socioeconomic interactions revealed by archeology. This pattern recapitulates the environmental and cultural differentiation between the fertile north, where altitudes are lower, and the arid south, where the Andes are higher, acting as a genetic barrier between the sharply different environments of the Andes and Amazonia. 2) The genetic homogenization between the populations of the arid Andes is not only due to migrations during the Inca Empire or the subsequent colonial period. It started at least during the earlier expansion of the Wari Empire (600 to 1,000 years before present). 3) This demographic history allowed for cases of positive natural selection in the high and arid Andes vs. the low Amazon tropical forest: in the Andes, a putative enhancer in HAND2-AS1 (heart and neural crest derivatives expressed 2 antisense RNA1, a noncoding gene related to cardiovascular function) and rs269868-C/Ser1067 in DUOX2 (dual oxidase 2, related to thyroid function and innate immunity) genes and, in the Amazon, the gene encoding for the CD45 protein, essential for antigen recognition by T and B lymphocytes in viral–host interaction. Significance Native Americans are neglected in human genetics studies, despite recent interest in the study of ancient DNA of their ancestors. Our findings on Andean and Amazonian populations exemplify how the current pattern of genetic diversity in human populations is influenced by the interaction of history and environment. In the present case, this pattern is influenced by 1) altitudinal and climatic differences among the northern, lower, and fertile Andes versus the southern, higher, and arid Andes and 2) the sharp differences between the Andean highlands and the Amazon lowlands, where natural selection and other evolutionary forces acted for millennia, shaping differences in the frequencies of genetic variants related to immune response, drug response, and cardiovascular and hematological functions.

Mitochondria are organelles that perform major roles in cellular operation. Thus, alterations in mitochondrial genome (mtGenome) may lead to mitochondrial dysfunction and cellular deregulation, influencing carcinogenesis. Gastric cancer (GC) is one of the most incident and mortal types of cancer in Brazil, particularly in the Amazon region. Here, we sequenced and compared the whole mtGenome extracted from FFPE tissue samples of GC patients (tumor and internal control – IC) and cancer-free individuals (external control – EC) from this region. We found 3-fold more variants and up to 9-fold more heteroplasmic regions in tumor when compared to paired IC samples. Moreover, tumor presented more heteroplasmic variants when compared to EC, while IC and EC showed no significant difference when compared to each other. Tumor also presented substantially more variants in the following regions: MT-RNR1, MT-ND5, MT-ND4, MT-ND2, MT-DLOOP1 and MT-CO1. In addition, our haplogroup results indicate an association of Native American ancestry (particularly haplogroup C) to gastric cancer development. To the best of our knowledge, this is the first study to sequence the whole mtGenome from FFPE samples and to apply mtGenome analysis in association to GC in Brazil.

Background: Mitochondrial participation in tumorigenesis and metastasis has been studied for many years, but several aspects of this mechanism remain unclear, such as the association of mitochondrial DNA (mtDNA) with different cancers. Here, based on two independent datasets, we modelled an mtDNA mutation-cancer network by systematic integrative analysis including 37 cancer types to identify the mitochondrial variants found in common among them. Results: Our network showed mtDNA associations between gastric cancer and other cancer types, particularly kidney, liver, and prostate cancers, which is suggestive of a potential role of such variants in the metastatic processes among these cancer types. A graph-based interactive web tool was made available at www2.lghm.ufpa.br/mtdna. We also highlighted that most shared variants were in the MT-ND4, MT-ND5 and D-loop, and that some of these variants were nonsynonymous, indicating a special importance of these variants and regions regarding cancer progression, involving genomic and epigenomic alterations. Conclusions: This study reinforces the importance of studying mtDNA in cancer and offers new perspectives on the potential involvement of different mitochondrial variants in cancer development and metastasis.

Background In recent years, deep learning has gained remarkable attention in medical image analysis due to its capacity to provide results comparable to specialists and, in some cases, surpass them. Despite the emergence of deep learning research on gastric tissues diseases, few intensive reviews are addressing this topic. Method We performed a systematic review related to applications of deep learning in gastric tissue disease analysis by digital histology, endoscopy and radiology images. Conclusions This review highlighted the high potential and shortcomings in deep learning research studies applied to gastric cancer, ulcer, gastritis and non-malignant diseases. Our results demonstrate the effectiveness of gastric tissue analysis by deep learning applications. Moreover, we also identified gaps of evaluation metrics, and image collection availability, therefore, impacting experimental reproducibility.