NAToRA, a relatedness-pruning method to minimize the loss of dataset size in genetic and omics analyses.

Genetic and omics analyses frequently require independent observations, which is not guaranteed in real datasets. When relatedness cannot be accounted for, solutions involve removing related individuals (or observations) and, consequently, a reduction of available data. We developed a network-based relatedness-pruning method that minimizes dataset reduction while removing unwanted relationships in a dataset. It uses node degree centrality metric to identify highly connected nodes (or individuals) and implements heuristics that approximate the minimal reduction of a dataset to allow its application to complex datasets. When compared with two other popular population genetics methodologies (PLINK and KING), NAToRA shows the best combination of removing all relatives while keeping the largest possible number of individuals in all datasets tested and also, with similar effects on the allele frequency spectrum and Principal Component Analysis than PLINK and KING. NAToRA is freely available, both as a standalone tool that can be easily incorporated as part of a pipeline, and as a graphical web tool that allows visualization of the relatedness networks. NAToRA also accepts a variety of relationship metrics as input, which facilitates its use. We also release a genealogies simulator software used for different tests performed in this study.

Population genetics of PDE4B (phosphodiesterase-4B) in neglected Native Americans: Implications for cancer pharmacogenetics.

PDE4B (phosphodiesterase-4B) has an important role in cancer and in pharmacology of some disorders, such as inflammatory diseases. Remarkably in Native Americans, PDE4B variants are associated with acute lymphoblastic leukemia (ALL) relapse, as this gene modulates sensitivity of glucocorticoids used in ALL chemotherapy. PDE4B allele rs6683977.G, associated with genomic regions of Native American origin in US-Hispanics (admixed among Native Americans, Europeans, and Africans), increases ALL relapse risk, contributing to an association between Native American ancestry and ALL relapse that disappeared with an extra-phase of chemotherapy. This result insinuates that indigenous populations along the Americas may have high frequencies of rs6683977.G, but this has never been corroborated. We studied ancestry and PDE4B diversity in 951 healthy individuals from nine Latin American populations. In non-admixed Native American populations rs6683977.G has frequencies greater than 90%, is in linkage disequilibrium with other ALL relapse associated and regulatory variants in PDE4B-intron-7, conforming haplotypes showing their highest worldwide frequencies in Native Americans (>0.82). Our findings inform the discussion on the pertinence of an extra-phase of chemotherapy in Native American populations, and exemplifies how knowledge generated in US-Hispanics is relevant for their even more neglected and vulnerable Native American ancestors along the American continent.

Seroprevalence, Prevalence, and Genomic Surveillance: Monitoring the Initial Phases of the SARS-CoV-2 Pandemic in Betim, Brazil.

The COVID-19 pandemic has created an unprecedented need for epidemiological monitoring using diverse strategies. We conducted a project combining prevalence, seroprevalence, and genomic surveillance approaches to describe the initial pandemic stages in Betim City, Brazil. We collected 3239 subjects in a population-based age-, sex- and neighborhood-stratified, household, prospective; cross-sectional study divided into three surveys 21 days apart sampling the same geographical area. In the first survey, overall prevalence (participants positive in serological or molecular tests) reached 0.46% (90% CI 0.12-0.80%), followed by 2.69% (90% CI 1.88-3.49%) in the second survey and 6.67% (90% CI 5.42-7.92%) in the third. The underreporting reached 11, 19.6, and 20.4 times in each survey. We observed increased odds to test positive in females compared to males (OR 1.88 95% CI 1.25-2.82), while the single best predictor for positivity was ageusia/anosmia (OR 8.12, 95% CI 4.72-13.98). Thirty-five SARS-CoV-2 genomes were sequenced, of which 18 were classified as lineage B.1.1.28, while 17 were B.1.1.33. Multiple independent viral introductions were observed. Integration of multiple epidemiological strategies was able to adequately describe COVID-19 dispersion in the city. Presented results have helped local government authorities to guide pandemic management.

Systematic review of host genetic association with Covid-19 prognosis and susceptibility: What have we learned in 2020?

Biomarker identification may provide strategic opportunities to understand disease pathophysiology, predict outcomes, improve human health, and reduce healthcare costs. The highly heterogeneous Covid-19 clinical manifestation suggests a complex interaction of several different human, viral and environmental factors. Here, we systematically reviewed genetic association studies evaluating Covid-19 severity or susceptibility to SARS-CoV-2 infection following PRISMA recommendations. Our research comprised papers published until December 31st , 2020, in PubMed and BioRXiv databases focusing on genetic association studies with Covid-19 prognosis or susceptibility. We found 20 eligible genetic association studies, of which 11 assessed Covid-19 outcome and 14 evaluated infection susceptibility (five analyzed both effects). Q-genie assessment indicated moderate quality. Five large-scale association studies (GWAS, whole-genome, or exome sequencing) were reported with no consistent replication to date. Promising hits were found on the 3p21.31 region and ABO locus. Candidate gene studies examined ACE1, ACE2, TMPRSS2, IFITM3, APOE, Furin, IFNL3, IFNL4, HLA, TNF-ɑ genes, and ABO system. The most evaluated single locus was the ABO, and the most sampled region was the HLA with three and five candidate gene studies, respectively. Meta-analysis could not be performed. Available data showed the need for further reports to replicate claimed associations.