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The N141I variant (PSEN1 gene) is associated with familial forms of early-onset Alzheimer's disease (AD) in descendants of Volga Germans, whose migration to Argentina is well documented. As a proxy for geographic origin, surnames can be a valuable tool in population studies. The 2015 Argentine Electoral Registry provided geographic data for 30,530,194 individuals, including 326,922 with Volga German surnames. Between 2005 and 2017, the Ministry of Health recorded 4,115,216 deaths, of which 17,226 were attributed to AD and related causes. The study used both diachronic and synchronic data to identify patterns of territorial distribution and co-spatiality, using Moran's I and generalised linear model statistics. The frequency of surnames of Volga German origin accounts for 43.53% of the variation in deaths from AD and three clusters of high non-random frequency were found. Almost 150 years later, people descending from the Volga migration remain highly concentrated and may have a different risk of developing AD. The identification of spatial patterns provides reliable guidance for medical research and highlights the importance of specific health policies for particular populations.

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BACKGROUND: Fetal deaths are a major source of information on the epidemiology of neural tube defects (NTDs; anencephaly and myelomeningocele). We analyzed NTDs prevalence and secular trend using fetal death records between 1994 and 2019 in Argentina. MATERIALS AND METHODS: Data were obtained from the Department of Statistics and Information of the Ministry of Health (DEIS). Using the number of fetal deaths due to anencephaly and myelomeningocele, we estimated the proportion of all fetal deaths due to anencephaly, myelomeningocele, and NTDs (anencephaly + myelomeningocele) during pre- and post-fortification period in Argentina. We also estimated the ratio of fetal deaths due to anencephaly, myelomeningocele, and NTDs (anencephaly + myelomeningocele) to 10,000 live births. Secular trend in the outcomes was analyzed using a Poisson model and Joinpoint regression analysis. RESULTS: In the entire period analyzed, the NTD proportion on fetal deaths was 1.32. In 1994, NTDs accounted for 34.7% of congenital malformations fetal deaths (CM) and 1.7% of all fetal deaths, whereas in 2019, these percentages were 9.4% and 0.5%, respectively. NTDs present a negative secular trend (p < .05). The risk of fetal death due to anencephaly and myelomeningocele decreases between 2005 and 2019 by 67% and 51% respectively (p < .05) in comparison to the period between 1994 and 2004 before the effective fortification of wheat flour used in the food industry destined for the domestic market. DISCUSSION AND CONCLUSION: We found a significant decrease in the risk of all fetal deaths due to NTDs, particularly anencephaly, in Argentina over the study period, with most reduction observed during the mandatory flour fortification era (introduced in Argentina in 2002). The inclusion of fetal deaths in NTD surveillance, coupled or uncoupled with other pregnancy outcomes, is essential for monitoring preventive supplementation measures.

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OBJECTIVES: To describe the frequency of hospitalizations of infants under 1 year of age with bronchiolitis in Puerto Madryn, Argentina, and to study the spatial distribution of cases throughout the city in relation to socioeconomic indicators. To visualize and better understand the underlying processes behind the local manifestation of the disease by creating a vulnerability map of the city. METHODS: We performed a cross-sectional study of all patients discharged for bronchiolitis from the local public Hospital in 2017, considering length of hospital stay, readmission rate, patient age, home address and socioeconomic indicators (household overcrowding). To understand the local spatial distribution of the disease and its relationship to overcrowding, we used GIS and Moran's global and local spatial autocorrelation indices. RESULTS: The spatial distribution of bronchiolitis cases was not random, but significantly aggregated. Of the 120 hospitalized children, 100 infants (83.33%) live in areas identified as having at least one unsatisfied basic need (UBN). We found a positive and statistically significant relationship between frequency of cases and percentage of overcrowded housing by census radius. CONCLUSIONS: A clear association was found between bronchiolitis and neighborhoods with UBNs, and overcrowding is likely to be a particularly important explanatory factor in this association. By combining GIS tools, spatial statistics, geo-referenced epidemiological data, and population-level information, vulnerability maps can be created to facilitate visualization of priority areas for development and implementation of more effective health interventions. Incorporating the spatial and syndemic perspective into health studies makes important contributions to the understanding of local health-disease processes.

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Self-perception of ethnicity is a complex social trait shaped by both, biological and non-biological factors. We developed a comprehensive analysis of ethnic self-perception (ESP) on a large sample of Latin American mestizos from five countries, differing in age, socio-economic and education context, external phenotypic attributes and genetic background. We measured the correlation of ESP against genomic ancestry, and the influence of physical appearance, socio-economic context, and education on the distortion observed between both. Here we show that genomic ancestry is correlated to aspects of physical appearance, which in turn affect the individual ethnic self-perceived ancestry. Also, we observe that, besides the significant correlation among genomic ancestry and ESP, specific physical or socio-economic attributes have a strong impact on self-perception. In addition, the distortion among ESP and genomic ancestry differs across age ranks/countries, probably suggesting the underlying effect of past public policies regarding identity. Our results indicate that individuals' own ideas about its origins should be taken with caution, especially in aspects of modern life, including access to work, social policies, and public health key decisions such as drug administration, therapy design, and clinical trials, among others.

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Haplogroup Q originated in Eurasia around 30,000 years ago. It is present in Y-chromosomes from Asia and Europe at rather low frequencies. Since America is undoubtedly one of the continents where this haplogroup is highly represented, it has been defined as one of the founding haplogroups. Its M3 clade has been early described as the most frequent, with pan-American representation. However, it was also possible to find several other haplogroup Q clades at low frequencies. Numerous mutations have been described for haplogroup Q, allowing analysis of its variability and assignment of its geographic origin. We have analyzed 442 samples of unrelated men from Argentina and Paraguay belonging to haplogroup Q; here we report specifically on 27 Q (xM3) lineages. We tested 3 single-nucleotide polymorphisms (SNPs) by amplified product-length polymorphism (APLP) analysis, 3 SNPs for restriction fragment length polymorphism (RFLP) analysis, 15 SNPs by Sanger sequencing, and 17 short tandem repeats (STRs). Our approach allowed us to identify five subhaplogroups. Q-M3 and Q-CTS2730/Z780 are undoubtedly autochthonous lineages and represent the most frequent subhaplogroups, with significant representation in self-defined aboriginal populations, and their autochthonous status has been previously described. The aim of present work was to identify the continental origin of the remaining Q lineages. Thus, we analyzed the STR haplotypes for the samples and compared them with haplotypes described by other authors for the rest of the world. Even when haplogroup Q lineages have been extensively studied in America, some of them could have their origin in post-Columbian human migration from Europe and Middle East.

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Several studies have shown that the Brazilian Northeast is a region with high rates of inbreeding as well as a high incidence of autosomal recessive diseases. The elaboration of public health policies focused on the epidemiological surveillance of congenital anomalies and rare genetic diseases in this region is urgently needed. However, the vast territory, socio-demographic heterogeneity, economic difficulties and low number of professionals with expertise in medical genetics make strategic planning a challenging task. Surnames can be compared to a genetic system with multiple neutral alleles and allow some approximation of population structure. Here, surname analysis of more than 37 million people was combined with health and socio-demographic indicators covering all 1794 municipalities of the nine states of the region. The data distribution showed a heterogeneous spatial pattern (Global Moran Index, GMI = 0.58; p < 0.001), with higher isonymy rates in the east of the region and the highest rates in the Quilombo dos Palmares region - the largest conglomerate of escaped slaves in Latin America. A positive correlation was found between the isonymy index and the frequency of live births with congenital anomalies (r = 0.268; p < 0.001), and the two indicators were spatially correlated (GMI = 0.50; p < 0.001). With this approach, quantitative information on the genetic structure of the Brazilian Northeast population was obtained, which may represent an economical and useful tool for decision-making in the medical field.

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Similarly to other populations across the Americas, Argentinean populations trace back their genetic ancestry into African, European and Native American ancestors, reflecting a complex demographic history with multiple migration and admixture events in pre- and post-colonial times. However, little is known about the sub-continental origins of these three main ancestries. We present new high-throughput genotyping data for 87 admixed individuals across Argentina. This data was combined to previously published data for admixed individuals in the region and then compared to different reference panels specifically built to perform population structure analyses at a sub-continental level. Concerning the Native American ancestry, we could identify four Native American components segregating in modern Argentinean populations. Three of them are also found in modern South American populations and are specifically represented in Central Andes, Central Chile/Patagonia, and Subtropical and Tropical Forests geographic areas. The fourth component might be specific to the Central Western region of Argentina, and it is not well represented in any genomic data from the literature. As for the European and African ancestries, we confirmed previous results about origins from Southern Europe, Western and Central Western Africa, and we provide evidences for the presence of Northern European and Eastern African ancestries.

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OBJECTIVES: The diagnosis and treatment of obesity are usually based on traditional anthropometric variables including weight, height, and several body perimeters. Here we present a three-dimensional (3D) image-based computational approach aimed to capture the distribution of abdominal adipose tissue as an aspect of shape rather than a relationship among classical anthropometric measures. METHODS: A morphometric approach based on landmarks and semilandmarks placed upon the 3D torso surface was performed in order to quantify abdominal adiposity shape variation and its relation to classical indices. Specifically, we analyzed sets of body cross-sectional circumferences, collectively defining each, along with anthropometric data taken on 112 volunteers. Principal Component Analysis (PCA) was performed on 250 circumferences located along the abdominal region of each volunteer. An analysis of covariance model was used to compare shape variables (PCs) against anthropometric data (weight, height, and waist and hip circumferences). RESULTS: The observed shape patterns were mainly related to nutritional status, followed by sexual dimorphism. PC1 (12.5%) and PC2 (7.5%) represented 20% of the total variation. In PCAs calculated independently by sex, linear regression analyses provide statistically significant associations between PC1 and the three classical indexes: body mass index, waist-to-height ratio, and waist-hip ratio. CONCLUSION: Shape indicators predict well the behavior of classical markers, but also evaluate 3D and geometric features with more accuracy as related to the body shape under study. This approach also facilitates diagnosis and follow-up of therapies by using accessible 3D technology.

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Current point cloud extraction methods based on photogrammetry generate large amounts of spurious detections that hamper useful 3D mesh reconstructions or, even worse, the possibility of adequate measurements. Moreover, noise removal methods for point clouds are complex, slow and incapable to cope with semantic noise. In this work, we present body2vec, a model-based body segmentation tool that uses a specifically trained Neural Network architecture. Body2vec is capable to perform human body point cloud reconstruction from videos taken on hand-held devices (smartphones or tablets), achieving high quality anthropometric measurements. The main contribution of the proposed workflow is to perform a background removal step, thus avoiding the spurious points generation that is usual in photogrammetric reconstruction. A group of 60 persons were taped with a smartphone, and the corresponding point clouds were obtained automatically with standard photogrammetric methods. We used as a 3D silver standard the clean meshes obtained at the same time with LiDAR sensors post-processed and noise-filtered by expert anthropological biologists. Finally, we used as gold standard anthropometric measurements of the waist and hip of the same people, taken by expert anthropometrists. Applying our method to the raw videos significantly enhanced the quality of the results of the point cloud as compared with the LiDAR-based mesh, and of the anthropometric measurements as compared with the actual hip and waist perimeter measured by the anthropometrists. In both contexts, the resulting quality of body2vec is equivalent to the LiDAR reconstruction.

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OBJECTIVES: This article aims to assess the contribution of genomic ancestry and socioeconomic status to obesity in a sample of admixed Latin Americans. METHODS: The study comprised 6776 adult volunteers from Brazil, Chile, Colombia, Mexico, and Peru. Each volunteer completed a questionnaire about socioeconomic variables. Anthropometric variables such as weight, height, waist, and hip circumference were measured to calculate body indices: body mass index, waist-to-hip ratio and waist-to-height ratio (WHtR). Genetic data were extracted from blood samples, and ancestry was estimated using chip genotypes. Multiple linear regression was used to evaluate the relationship between the indices and ancestry, educational level, and economic well-being. The body indices were dichotomized to obesity indices by using appropriate thresholds. Odds ratios were calculated for each obesity index. RESULTS: The sample showed high percentages of obesity by all measurements. However, indices did not overlap consistently when classifying obesity. WHtR resulted in the highest prevalence of obesity. Overall, women with low education level and men with high economic wellness were more likely to be obese. American ancestry was statistically associated with obesity indices, although to a lesser extent than socioeconomic variables. CONCLUSIONS: The proportion of obesity was heavily dependent on the index and the population. Genomic ancestry has a significant influence on the anthropometric measurements, especially on central adiposity. As a whole, we detected a large interpopulation variation that suggests that better approaches to overweight and obesity phenotypes are needed in order to obtain more precise reference values.

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