scholarly journals An Emergent Integrated Aging Process Conserved Across Primates

2019 ◽  
Vol 74 (11) ◽  
pp. 1689-1698 ◽  
Author(s):  
Tina W Wey ◽  
Émy Roberge ◽  
Véronique Legault ◽  
Joseph W Kemnitz ◽  
Luigi Ferrucci ◽  
...  
Keyword(s):  
Mortality Risk ◽  
Aging Process ◽  
Principal Component ◽  
Physiological Process ◽  
Primate Species ◽  
Human Populations ◽  
Complex Process ◽  
Evolutionarily Conserved ◽  
Primary Axis ◽  
Negative Impacts

Abstract Aging is a complex process emerging from integrated physiological networks. Recent work using principal component analysis (PCA) of multisystem biomarkers proposed a novel fundamental physiological process, “integrated albunemia,” which was consistent across human populations and more strongly associated with age and mortality risk than individual biomarkers. Here we tested for integrated albunemia and associations with age and mortality across six diverse nonhuman primate species and humans. PCA of 13 physiological biomarkers recovered in all species a primary axis of variation (PC1) resembling integrated albunemia, which increased with age in all but one species but was less predictive of mortality risk. Within species, PC1 scores were often reliably recovered with a minimal biomarker subset and usually stable between sexes. Even among species, correlations in PC1 structure were often strong, but the effect of phylogeny was inconclusive. Thus, integrated albunemia likely reflects an evolutionarily conserved process across primates and appears to be generally associated with aging but not necessarily with negative impacts on survival. Integrated albunemia is unlikely to be the only conserved emergent physiological process; our findings hence have implications both for the evolution of the aging process and of physiological networks more generally.

scholarly journals Genome-wide SNP data of Izumo and Makurazaki populations support inner-dual structure model for origin of Yamato people

2021 ◽  
Author(s):  
Timothy Jinam ◽  
Yosuke Kawai ◽  
Yoichiro Kamatani ◽  
Shunro Sonoda ◽  
Kanro Makisumi ◽  
...  
Keyword(s):  
Phylogenetic Network ◽  
Principal Component ◽  
Human Populations ◽  
Structure Model ◽  
Rice Farming ◽  
Asian Continent ◽  
Dual Structure ◽  
Snp Data ◽  
Genome Wide ◽  
Kagoshima Prefecture

AbstractThe “Dual Structure” model on the formation of the modern Japanese population assumes that the indigenous hunter-gathering population (symbolized as Jomon people) admixed with rice-farming population (symbolized as Yayoi people) who migrated from the Asian continent after the Yayoi period started. The Jomon component remained high both in Ainu and Okinawa people who mainly reside in northern and southern Japan, respectively, while the Yayoi component is higher in the mainland Japanese (Yamato people). The model has been well supported by genetic data, but the Yamato population was mostly represented by people from Tokyo area. We generated new genome-wide SNP data using Japonica Array for 45 individuals in Izumo City of Shimane Prefecture and for 72 individuals in Makurazaki City of Kagoshima Prefecture in Southern Kyushu, and compared these data with those of other human populations in East Asia, including BioBank Japan data. Using principal component analysis, phylogenetic network, and f4 tests, we found that Izumo, Makurazaki, and Tohoku populations are slightly differentiated from Kanto (including Tokyo), Tokai, and Kinki regions. These results suggest the substructure within Mainland Japanese maybe caused by multiple migration events from the Asian continent following the Jomon period, and we propose a modified version of “Dual Structure” model called the “Inner-Dual Structure” model.

scholarly journals The food patterns of a multicenter cohort of Brazilian nulliparous pregnant women

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Maria J. Miele ◽  
Renato T. Souza ◽  
Iracema M. Calderon ◽  
Francisco E. Feitosa ◽  
Débora F. Leite ◽  
...  
Keyword(s):  
Pregnant Women ◽  
Dietary Patterns ◽  
Principal Component ◽  
Good Representation ◽  
Processed Foods ◽  
Food Groups ◽  
Dietary Recall ◽  
Complex Process ◽  
Nutrient Consumption ◽  
Main Components

AbstractAssessment of human nutrition is a complex process, in pregnant women identify dietary patterns through mean nutrient consumption can be an opportunity to better educate women on how to improve their overall health through better eating. This exploratory study aimed to identify a posteriori dietary patterns in a cohort of nulliparous pregnant women. The principal component analysis (PCA) technique was performed, with Varimax orthogonal rotation of data extracted from the 24-h dietary recall, applied at 20 weeks of gestation. We analysed 1.145 dietary recalls, identifying five main components that explained 81% of the dietary pattern of the sample. Dietary patterns found were: Obesogenic, represented by ultra-processed foods, processed foods, and food groups rich in carbohydrates, fats and sugars; Traditional, most influenced by natural, minimally processed foods, groups of animal proteins and beans; Intermediate was similar to the obesogenic, although there were lower loads; Vegetarian, which was the only good representation of fruits, vegetables and dairy products; and Protein, which best represented the groups of proteins (animal and vegetable). The obesogenic and intermediate patterns represented over 37% of the variation in food consumption highlighting the opportunity to improve maternal health especially for women at first mothering.

scholarly journals Detecting selection in low-coverage high-throughput sequencing data using principal component analysis

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Jonas Meisner ◽  
Anders Albrechtsen ◽  
Kristian Hanghøj
Keyword(s):  
Principal Component Analysis ◽  
High Throughput ◽  
East Asian ◽  
Principal Component ◽  
Component Analysis ◽  
Human Populations ◽  
Population Genetic Study ◽  
Sequencing Data ◽  
High Quality ◽  
Low Coverage

Abstract Background Identification of selection signatures between populations is often an important part of a population genetic study. Leveraging high-throughput DNA sequencing larger sample sizes of populations with similar ancestries has become increasingly common. This has led to the need of methods capable of identifying signals of selection in populations with a continuous cline of genetic differentiation. Individuals from continuous populations are inherently challenging to group into meaningful units which is why existing methods rely on principal components analysis for inference of the selection signals. These existing methods require called genotypes as input which is problematic for studies based on low-coverage sequencing data. Materials and methods We have extended two principal component analysis based selection statistics to genotype likelihood data and applied them to low-coverage sequencing data from the 1000 Genomes Project for populations with European and East Asian ancestry to detect signals of selection in samples with continuous population structure. Results Here, we present two selections statistics which we have implemented in the framework. These methods account for genotype uncertainty, opening for the opportunity to conduct selection scans in continuous populations from low and/or variable coverage sequencing data. To illustrate their use, we applied the methods to low-coverage sequencing data from human populations of East Asian and European ancestries and show that the implemented selection statistics can control the false positive rate and that they identify the same signatures of selection from low-coverage sequencing data as state-of-the-art software using high quality called genotypes. Conclusion We show that selection scans of low-coverage sequencing data of populations with similar ancestry perform on par with that obtained from high quality genotype data. Moreover, we demonstrate that outperform selection statistics obtained from called genotypes from low-coverage sequencing data without the need for ad-hoc filtering.

scholarly journals Oxidative Stress Risk Is Increased with a Sedentary Lifestyle during Aging in Mexican Women

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Martha A. Sánchez-Rodríguez ◽  
Mariano Zacarías-Flores ◽  
Elsa Correa-Muñoz ◽  
Alicia Arronte-Rosales ◽  
Víctor Manuel Mendoza-Núñez
Keyword(s):  
Oxidative Stress ◽  
Physical Activity ◽  
Aging Process ◽  
Sedentary Lifestyle ◽  
Principal Component ◽  
Poisson Model ◽  
Community Dwelling ◽  
Mexican Women ◽  
The Difference

Oxidative stress (OS) increases during the human aging process, and the sedentary lifestyle could be a prooxidant factor. In this study, we determine the effect of sedentary lifestyle on OS during the aging process in Mexican women. A longitudinal study of two-year follow-up was carried out with 177 community-dwelling women (40-69 y) from Mexico City. We measured as OS markers plasma malondialdehyde, erythrocyte glutathione peroxidase (GPx) and superoxide dismutase (SOD), total plasma antioxidant status, uric acid level, antioxidant gap, and SOD/GPx ratio. To define OS using all the markers, we defined cut-off values of each parameter based on the 90th percentile of young healthy subjects and, we calculated a stress score (SS) ranging from 0 to 7, which represented the intensity of the marker modifications. All the women answered a structured questionnaire about prooxidant factors, including physical activity specially the type of activity, frequency, and duration, and they answered Spanish versions of self-assessment tests for establishing dysthymia and insomnia as potential confounders. Principal component and Poisson regression analysis were used as statistical tools, being two-year OS the primary outcome. The OS was considerate as SS ≥ 4 and sedentary lifestyle as <30 min/day of physical activity, beside several prooxidant factors and age that were covariables. SS is higher in sedentary lifestyle women after the two-year follow-up; although, the difference was statistically significant only in older women. Four principal components were associated with the OS, and 7 out of 8 prooxidant factors were important for the analysis, which were included in the Poisson model. The predictive factors for OS were the sedentary lifestyle (adjusted PR = 2.37, CI95%: 1.30–4.30, p < 0.01 ), and age, in which the risk increases 1.06 (CI95%:1.02–2.11, p < 0.01 ) by each year of age. Our findings suggest that a sedentary lifestyle increases the OS during the aging in Mexican women.

ENSO and the Spatial Extent of Interannual Precipitation Extremes in Tropical Land Areas

2005 ◽  
Vol 18 (23) ◽  
pp. 5095-5109 ◽  
Author(s):  
Bradfield Lyon ◽  
Anthony G. Barnston
Keyword(s):  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Standardized Precipitation Index ◽  
Precipitation Extremes ◽  
Spatial Extent ◽  
Human Populations ◽  
Enso Events ◽  
Dry Conditions ◽  
Negative Impacts

Abstract The extreme phases of El Niño–Southern Oscillation (ENSO) are known to dominate the interannual variability of tropical rainfall. However, the relationship between ENSO and the spatial extent of drought and excessively wet conditions is an important characteristic of the tropical climate that has received relatively less attention from researchers. Here, a standardized precipitation index is computed from monthly rainfall analyses and the temporal variability of the spatial extent of such extremes, for various levels of severity, is examined from a Tropics-wide perspective (land areas only, 30°S–30°N). Maxima in the spatial extent of both precipitation extremes are compared across multiple ENSO events that occurred during the period 1950–2003. The focus on tropical land areas is motivated by the numerous, often negative, impacts of ENSO-related precipitation variability on human populations. Results show that major peaks in the spatial extent of drought and excessively wet conditions are generally associated with extreme phases of ENSO. A remarkably robust linear relationship is documented between the spatial extent of drought in the Tropics and El Niño strength (based on Niño-3.4 sea surface temperature anomalies), with a comparatively weaker relationship for La Niña and excessive wetness. Both conditions are found to increase by about a factor of 2 between strong and weak ENSO events, and in several locations they are shown to be more likely during ENSO events than at all other times, especially for severe categories. Relatively stronger El Niño events during recent decades are associated with increased drought extent in tropical land areas with increasing surface temperatures likely acting to exacerbate these dry conditions.

CONSANGUINITY BY RANDOM ISONYMY AND SOCIOECONOMIC DEVELOPMENT IN ARGENTINA: A POPULATION STUDY

2016 ◽  
Vol 49 (3) ◽  
pp. 322-333 ◽  
Author(s):  
José Edgardo Dipierri ◽  
Alvaro Rodríguez-Larralde ◽  
Italo Barrai ◽  
Esperanza Gutiérrez Redomero ◽  
Concepción Alonso-Rodríguez ◽  
...  
Keyword(s):  
Socioeconomic Development ◽  
Principal Component ◽  
Economic Indicator ◽  
Demographic Variables ◽  
Human Populations ◽  
Socioeconomic Conditions ◽  
Administrative Organization ◽  
The North ◽  
The Relationship ◽  
Different Levels

SummaryIn human populations various flexible, labile and interdependent structures (genetic, demographic, socioeconomic) co-exist, each of which can be organized in an hierarchical order corresponding to administrative entities. The relationship between consanguinity, as estimated by random isonymy (FST), and socioeconomic conditions was analysed at different levels of political and administrative organization in Argentina. From the surnames of 22,666,139 voters from the 2001 electoral roll,FSTwas estimated for 510 Argentinian departments. Using a principal component analysis, a Socio-Demographic and Economic Indicator (SDEI), summarizing the effect of 22 socioeconomic and demographic variables at the departmental level, was computed. The relationship between departmentalFSTand SDEI values was analysed for the whole nation and within regions using multiple regression analysis. TheFSTpresented a clinal distribution with the highest values in the north and west of the country, while SDEI expressed the opposite behaviour. A negative and significant correlation was observed betweenFSTand SDEI, accounting for 46% of the variation in consanguinity in Argentina. The strongest correlations ofFSTwith SDEI were observed in the Central, Patagonia and Cuyo regions, i.e. those with the highest values of SDEI and lowest values ofFST.

scholarly journals Dam Policy: The Need For Global Governance

2013 ◽  
Vol 2 (2) ◽  
pp. 31-38 ◽  
Author(s):  
Peter Longo ◽  
Richard Cummings
Keyword(s):  
Food Production ◽  
Negative Impact ◽  
Environmental Accounting ◽  
Global Perspective ◽  
Human Populations ◽  
Hydroelectric Power ◽  
Policy Makers ◽  
Global Policy ◽  
Negative Impacts ◽  
Physical Construction

Dams have long fascinated engineers, policymakers, and citizens-at-large. No doubt the engineering and architectural details of physical construction of dams are worth study and scrutiny, but it is the human dimension that complicates dam policies. Dams can result in tremendous negative impacts on human populations. Yet, dams provide a source of renewable energy, hydroelectric power. Analyzing these issues in a global perspective offers strategies for policy makers to consider. This paper will analyze the negative impact dams have on humans, illustrate the hydroelectric push for dams and how they impact food production. Finally, global policy strategies will be offered with consideration of environmental accounting and an indication of the future of water and food.

scholarly journals Impacts of biodiversity and biodiversity loss on zoonotic diseases

2021 ◽  
Vol 118 (17) ◽  
pp. e2023540118
Author(s):  
Felicia Keesing ◽  
Richard S. Ostfeld
Keyword(s):  
Human Health ◽  
Disease Risk ◽  
Human Impacts ◽  
Biodiversity Loss ◽  
Zoonotic Diseases ◽  
Human Populations ◽  
Zoonotic Pathogens ◽  
New Synthesis ◽  
Negative Impacts ◽  
Opposing Effects

Zoonotic diseases are infectious diseases of humans caused by pathogens that are shared between humans and other vertebrate animals. Previously, pristine natural areas with high biodiversity were seen as likely sources of new zoonotic pathogens, suggesting that biodiversity could have negative impacts on human health. At the same time, biodiversity has been recognized as potentially benefiting human health by reducing the transmission of some pathogens that have already established themselves in human populations. These apparently opposing effects of biodiversity in human health may now be reconcilable. Recent research demonstrates that some taxa are much more likely to be zoonotic hosts than others are, and that these animals often proliferate in human-dominated landscapes, increasing the likelihood of spillover. In less-disturbed areas, however, these zoonotic reservoir hosts are less abundant and nonreservoirs predominate. Thus, biodiversity loss appears to increase the risk of human exposure to both new and established zoonotic pathogens. This new synthesis of the effects of biodiversity on zoonotic diseases presents an opportunity to articulate the next generation of research questions that can inform management and policy. Future studies should focus on collecting and analyzing data on the diversity, abundance, and capacity to transmit of the taxa that actually share zoonotic pathogens with us. To predict and prevent future epidemics, researchers should also focus on how these metrics change in response to human impacts on the environment, and how human behaviors can mitigate these effects. Restoration of biodiversity is an important frontier in the management of zoonotic disease risk.

scholarly journals Current and Future Concepts for the Treatment of Impaired Fracture Healing

2019 ◽  
Vol 20 (22) ◽  
pp. 5805 ◽  
Author(s):  
Carsten W. Schlickewei ◽  
Holger Kleinertz ◽  
Darius M. Thiesen ◽  
Konrad Mader ◽  
Matthias Priemel ◽  
...  
Keyword(s):  
Fracture Healing ◽  
Bone Regeneration ◽  
Treatment Options ◽  
Surgical Techniques ◽  
Therapeutic Approaches ◽  
Economic Implications ◽  
Complex Process ◽  
Number Of Patients ◽  
Evolutionarily Conserved ◽  
Future Concepts

Bone regeneration represents a complex process, of which basic biologic principles have been evolutionarily conserved over a broad range of different species. Bone represents one of few tissues that can heal without forming a fibrous scar and, as such, resembles a unique form of tissue regeneration. Despite a tremendous improvement in surgical techniques in the past decades, impaired bone regeneration including non-unions still affect a significant number of patients with fractures. As impaired bone regeneration is associated with high socio-economic implications, it is an essential clinical need to gain a full understanding of the pathophysiology and identify novel treatment approaches. This review focuses on the clinical implications of impaired bone regeneration, including currently available treatment options. Moreover, recent advances in the understanding of fracture healing are discussed, which have resulted in the identification and development of novel therapeutic approaches for affected patients.

scholarly journals Genotypes of informative loci from 1000 Genomes data allude evolution and mixing of human populations

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sridevi Padakanti ◽  
Khong-Loon Tiong ◽  
Yan-Bin Chen ◽  
Chen-Hsiang Yeang
Keyword(s):  
Population Distribution ◽  
Principal Component ◽  
Functional Enrichment ◽  
Weighted Sums ◽  
Small Subset ◽  
Human Populations ◽  
Demographic Model ◽  
Genotype Data ◽  
Founder Population ◽  
1000 Genomes

AbstractPrincipal Component Analysis (PCA) projects high-dimensional genotype data into a few components that discern populations. Ancestry Informative Markers (AIMs) are a small subset of SNPs capable of distinguishing populations. We integrate these two approaches by proposing an algorithm to identify necessary informative loci whose removal from the data deteriorates the PCA structure. Unlike classical AIMs, necessary informative loci densely cover the genome, hence can illuminate the evolution and mixing history of populations. We conduct a comprehensive analysis to the genotype data of the 1000 Genomes Project using necessary informative loci. Projections along the top seven principal components demarcate populations at distinct geographic levels. Millions of necessary informative loci along each PC are identified. Population identities along each PC are approximately determined by weighted sums of minor (or major) alleles over the informative loci. Variations of allele frequencies are aligned with the history and direction of population evolution. The population distribution of projections along the top three PCs is recapitulated by a simple demographic model based on several waves of founder population separation and mixing. Informative loci possess locational concentration in the genome and functional enrichment. Genes at two hot spots encompassing dense PC 7 informative loci exhibit differential expressions among European populations. The mosaic of local ancestry in the genome of a mixed descendant from multiple populations can be inferred from partial PCA projections of informative loci. Finally, informative loci derived from the 1000 Genomes data well predict the projections of an independent genotype data of South Asians. These results demonstrate the utility and relevance of informative loci to investigate human evolution.

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