Human serum metabolic profiles are age dependent

Understanding the complexity of aging is of utmost importance. This can now be addressed by the novel and powerful approach of metabolomics. However, to date, only a few metabolic studies based on large samples are available. Here, we provide novel and specific information on age-related metabolite concentration changes in human homeostasis. We report results from two population-based studies: the KORA F4 study from Germany as a discovery cohort, with 1038 female and 1124 male participants (32–81 years), and the TwinsUK study as replication, with 724 female participants. Targeted metabolomics of fasting serum samples quantified 131 metabolites by FIA-MS/MS. Among these, 71/34 metabolites were significantly associated with age in women/men (BMI adjusted). We further identified a set of 13 independent metabolites in women (with P values ranging from 4.6 × 10−04 to 7.8 × 10−42, αcorr = 0.004). Eleven of these 13 metabolites were replicated in the TwinsUK study, including seven metabolite concentrations that increased with age (C0, C10:1, C12:1, C18:1, SM C16:1, SM C18:1, and PC aa C28:1), while histidine decreased. These results indicate that metabolic profiles are age dependent and might reflect different aging processes, such as incomplete mitochondrial fatty acid oxidation. The use of metabolomics will increase our understanding of aging networks and may lead to discoveries that help enhance healthy aging

Social stratification without genetic differentiation at the site of Kulubnarti in Christian Period Nubia

Relatively little is known about Nubia’s genetic landscape prior to the influence of the Islamic migrations that began in the late 1st millennium CE. Here, we increase the number of ancient individuals with genome-level data from the Nile Valley from three to 69, reporting data for 66 individuals from two cemeteries at the Christian Period (~650–1000 CE) site of Kulubnarti, where multiple lines of evidence suggest social stratification. The Kulubnarti Nubians had ~43% Nilotic-related ancestry (individual variation between ~36–54%) with the remaining ancestry consistent with being introduced through Egypt and ultimately deriving from an ancestry pool like that found in the Bronze and Iron Age Levant. The Kulubnarti gene pool – shaped over a millennium – harbors disproportionately female-associated West Eurasian-related ancestry. Genetic similarity among individuals from the two cemeteries supports a hypothesis of social division without genetic distinction. Seven pairs of inter-cemetery relatives suggest fluidity between cemetery groups. Present-day Nubians are not directly descended from the Kulubnarti Nubians, attesting to additional genetic input since the Christian Period.K.A.S. was supported by a Doctoral Dissertation Research Improvement Grant from the National Science Foundation (BCS-1613577). D.R. was funded by NSF HOMINID grant BCS-1032255; NIH (NIGMS) grant GM100233; the Allen Discovery Center program, a Paul G. Allen Frontiers Group advised program of the Paul G. Allen Family Foundation; the John Templeton Foundation grant 61220; and the Howard Hughes Medical Institute

Ancient genomes in South Patagonia reveal population movements associated with technological shifts and geography

Archaeological research documents major technological shifts among people who have lived in the southern tip of South America (South Patagonia) during the last thirteen millennia, including the development of marine-based economies and changes in tools and raw materials. It has been proposed that movements of people spreading culture and technology propelled some of these shifts, but these hypotheses have not been tested with ancient DNA. Here we report genome-wide data from 20 ancient individuals, and co-analyze it with previously reported data. We reveal that immigration does not explain the appearance of marine adaptations in South Patagonia. We describe partial genetic continuity since ~6600 BP and two later gene flows correlated with technological changes: one between 4700–2000 BP that affected primarily marine-based groups, and a later one impacting all <2000 BP groups. From ~2200–1200 BP, mixture among neighbors resulted in a cline correlated to geographic ordering along the coast.Fil: Nakatsuka, Nathan. Harvard Medical School; Estados UnidosFil: Luisi, Pierre. Universidad Nacional de Córdoba. Facultad de Filosofía y Humanidades; ArgentinaFil: Motti, Josefina María Brenda. Universidad Nacional del Centro de la Provincia de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Salemme, Monica Cira. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas; Argentina. Universidad Nacional de Tierra del Fuego; ArgentinaFil: Santiago, Fernando Carlos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas; ArgentinaFil: D'angelo del Campo, Manuel Domingo. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Sociales. Grupo de Estudios Interdisciplinarios sobre Poblaciones Humanas de Patagonia Austral; Argentina. Universidad Autónoma de Madrid; EspañaFil: Vecchi, Rodrigo Javier. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Sur; ArgentinaFil: Espinosa Parrilla, Yolanda. Consejo Superior de Investigaciones Científicas; EspañaFil: Prieto, Alfredo. Universidad de Magallanes; ChileFil: Adamski, Nicole. Harvard Medical School; Estados UnidosFil: Lawson, Ann Marie. Harvard Medical School; Estados UnidosFil: Harper, Thomas K.. University of Pennsylvania; Estados UnidosFil: Culleton, Brendan J.. University of Pennsylvania; Estados UnidosFil: Kennett, Douglas J.. University of California; Estados UnidosFil: Lalueza Fox, Carles. Consejo Superior de Investigaciones Científicas; EspañaFil: Mallick, Swapan. Harvard Medical School; Estados UnidosFil: Rohland, Nadin. Harvard Medical School; Estados UnidosFil: Guichón, Ricardo A.. Universidad Nacional del Centro de la Provincia de Buenos Aires; ArgentinaFil: Cabana, Graciela S.. University of Tennessee; Estados UnidosFil: Nores, Rodrigo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Antropología de Córdoba. Universidad Nacional de Córdoba. Facultad de Filosofía y Humanidades. Instituto de Antropología de Córdoba; ArgentinaFil: Reich, David. Harvard Medical School. Department Of Medicine; Estados Unido

The genomic history of the Iberian Peninsula over the past 8000 years

We assembled genome-wide data from 271 ancient Iberians, of whom 176 are from the largely unsampled period after 2000 BCE, thereby providing a high-resolution time transect of the Iberian Peninsula.We document high genetic substructure between northwestern and southeastern hunter-gatherers before the spread of farming.We reveal sporadic contacts between Iberia and North Africa by ~2500 BCE and, by ~2000 BCE, the replacement of 40% of Iberia's ancestry and nearly 100% of its Y-chromosomes by people with Steppe ancestry.We show that, in the Iron Age, Steppe ancestry had spread not only into Indo-European-speaking regions but also into non-Indo-European-speaking ones, and we reveal that present-day Basques are best described as a typical Iron Age population without the admixture events that later affected the rest of Iberia. Additionally, we document how, beginning at least in the Roman period, the ancestry of the peninsula was transformed by gene flow from North Africa and the eastern Mediterranean

Reconstructing the Deep Population History of Central and South America

We report genome-wide ancient DNA from 49 individuals forming four parallel time transects in Belize, Brazil, the Central Andes, and the Southern Cone, each dating to at least 9,000 years ago. The common ancestral population radiated rapidly from just one of the two early branches that contributed to Native Americans today. We document two previously unappreciated streams of gene flow between North and South America. One affected the Central Andes by 4,200 years ago, while the other explains an affinity between the oldest North American genome associated with the Clovis culture and the oldest Central and South Americans from Chile, Brazil, and Belize. However, this was not the primary source for later South Americans, as the other ancient individuals derive from lineages without specific affinity to the Clovis-associated genome, suggesting a population replacement that began at least 9,000 years ago and was followed by substantial population continuity in multiple regions

A genetic history of the pre-contact Caribbean

Humans settled the Caribbean about 6,000 years ago, and ceramic use and intensified agriculture mark a shift from the Archaic to the Ceramic Age at around 2,500 years ago1,2,3. Here we report genome-wide data from 174 ancient individuals from The Bahamas, Haiti and the Dominican Republic (collectively, Hispaniola), Puerto Rico, Curaçao and Venezuela, which we co-analysed with 89 previously published ancient individuals. Stone-tool-using Caribbean people, who first entered the Caribbean during the Archaic Age, derive from a deeply divergent population that is closest to Central and northern South American individuals; contrary to previous work4, we find no support for ancestry contributed by a population related to North American individuals. Archaic-related lineages were >98% replaced by a genetically homogeneous ceramic-using population related to speakers of languages in the Arawak family from northeast South America; these people moved through the Lesser Antilles and into the Greater Antilles at least 1,700 years ago, introducing ancestry that is still present. Ancient Caribbean people avoided close kin unions despite limited mate pools that reflect small effective population sizes, which we estimate to be a minimum of 500–1,500 and a maximum of 1,530–8,150 individuals on the combined islands of Puerto Rico and Hispaniola in the dozens of generations before the individuals who we analysed lived. Census sizes are unlikely to be more than tenfold larger than effective population sizes, so previous pan-Caribbean estimates of hundreds of thousands of people are too large5,6. Confirming a small and interconnected Ceramic Age population7, we detect 19 pairs of cross-island cousins, close relatives buried around 75 km apart in Hispaniola and low genetic differentiation across islands. Genetic continuity across transitions in pottery styles reveals that cultural changes during the Ceramic Age were not driven by migration of genetically differentiated groups from the mainland, but instead reflected interactions within an interconnected Caribbean world1,8.This work was supported by a grant from the National Geographic Society to M. Pateman to facilitate analysis of skeletal material from The Bahamas and by a grant from the Italian ‘Ministry of Foreign Affairs and International Cooperation’ (Italian archaeological, anthropological and ethnological missions abroad, DGPSP Ufficio VI). D.R. was funded by NSF HOMINID grant BCS-1032255, NIH (NIGMS) grant GM100233, the Paul Allen Foundation, the John Templeton Foundation grant 61220 and the Howard Hughes Medical Institute.Peer reviewe

Genomic Insights into the Formation of Human Populations in East Asia

厦门大学人类学研究所、厦门大学生命科学学院细胞应激生物学国家重点实验室王传超教授课题组与哈佛医学院David Reich教授团队合作，联合全球43个单位的85位共同作者组成的国际合作团队通过古DNA精细解析东亚人群形成历史。研究人员利用古DNA数据检验了东亚地区农业和语言共扩散理论，综合考古学、语言学等证据，该研究系统性地重构了东亚人群的形成、迁徙和混合历史。这是目前国内开展的东亚地区最大规模的考古基因组学研究，此次所报道的东亚地区古人基因组样本量是以往国内研究机构所发表的样本量总和的两倍，改变了东亚地区尤其是中国境内考古基因组学研究长期滞后的局面。 该研究是由王传超教授团队与哈佛医学院（David Reich教授）、德国马普人类历史科学研究所（Johannes Krause教授）、复旦大学现代人类学教育部重点实验室（李辉教授和金力院士）、维也纳大学进化人类学系（Ron Pinhasi副教授）、南洋理工大学人文学院（Hui-Yuan Yeh助理教授）、俄罗斯远东联邦大学科学博物馆（Alexander N Popov研究员）、西安交通大学（张虎勤教授）、蒙古国国家博物馆研究中心、乌兰巴托国立大学考古系、华盛顿大学人类学系、台湾成功大学考古所、加州大学人类学系等全球43个单位的85位共同作者组成的国际合作团队联合完成的。厦门大学人类学研究所、厦门大学生命科学学院细胞应激生物学国家重点实验室为论文第一完成单位。厦门大学人类学研究所韦兰海副教授、胡荣助理教授、郭健新博士后、何光林博士后和杨晓敏硕士参与了研究工作。The deep population history of East Asia remains poorly understood due to a lack of ancient DNA data and sparse sampling of present-day people1,2. We report genome-wide data from 166 East Asians dating to 6000 BCE-1000 CE and 46 present-day groups. Hunter-gatherers from Japan, the Amur River Basin, and people of Neolithic and Iron Age Taiwan and the Tibetan plateau are linked by a deeply-splitting lineage likely reflecting a Late Pleistocene coastal migration. We follow Holocene expansions from four regions. First, hunter-gatherers of Mongolia and the Amur River Basin have ancestry shared by Mongolic and Tungusic language speakers but do not carry West Liao River farmer ancestry contradicting theories that their expansion spread these proto-languages. Second, Yellow River Basin farmers at ～3000 BCE likely spread Sino-Tibetan languages as their ancestry dispersed both to Tibet where it forms up ～84% to some groups and to the Central Plain where it contributed ～59-84% to Han Chinese. Third, people from Taiwan ～1300 BCE to 800 CE derived ～75% ancestry from a lineage also common in modern Austronesian, Tai-Kadai and Austroasiatic speakers likely deriving from Yangtze River Valley farmers; ancient Taiwan people also derived ～25% ancestry from a northern lineage related to but different from Yellow River farmers implying an additional north-to-south expansion. Fourth, Yamnaya Steppe pastoralist ancestry arrived in western Mongolia after ～3000 BCE but was displaced by previously established lineages even while it persisted in western China as expected if it spread the ancestor of Tocharian Indo-European languages. Two later gene flows affected western Mongolia: after ～2000 BCE migrants with Yamnaya and European farmer ancestry, and episodic impacts of later groups with ancestry from Turan.We thank David Anthony, Ofer Bar-Yosef, Katherine Brunson, Rowan Flad, Pavel Flegontov,Qiaomei Fu, Wolfgang Haak, Iosif Lazaridis, Mark Lipson, Iain Mathieson, Richard Meadow,Inigo Olalde, Nick Patterson, Pontus Skoglund, Dan Xu, and the four reviewers for valuable comments. We thank Naruya Saitou and the Asian DNA Repository Consortium for sharing genotype data from present-day Japanese groups. We thank Toyohiro Nishimoto and Takashi Fujisawa from the Rebun Town Board of Education for sharing the Funadomari Jomon samples, and Hideyo Tanaka and Watru Nagahara from the Archeological Center of Chiba City who are excavators of the Rokutsu Jomon site. The excavations at Boisman-2 site (Boisman culture), the Pospelovo-1 site (Yankovsky culture), and the Roshino-4 site (Heishui Mohe culture) were funded by the Far Eastern Federal University and the Institute of History,Archaeology and Ethnology Far Eastern Branch of the Russian Academy of Sciences; research on Pospelovo-1 is funded by RFBR project number 18-09-40101. C.C.W was funded by the Max Planck Society, the National Natural Science Foundation of China (NSFC 31801040), the Nanqiang Outstanding Young Talents Program of Xiamen University (X2123302), the Major project of National Social Science Foundation of China (20&ZD248), a European Research Council (ERC) grant to Dan Xu (ERC-2019-ADG-883700-TRAM) and Fundamental Research Funds for the Central Universities (ZK1144). O.B. and Y.B. were funded by Russian Scientific Foundation grant 17-14-01345. H.M. was supported by the grant JSPS 16H02527. M.R. and C.C.W received funding from the ERC under the European Union’s Horizon 2020 research and innovation program (grant No 646612) to M.R. The research of C.S. is supported 30 by the Calleva Foundation and the Human Origins Research Fund. H.L was funded NSFC (91731303, 31671297), B&R International Joint Laboratory of Eurasian Anthropology (18490750300). J.K. was funded by DFG grant KR 4015/1-1, the Baden Württemberg Foundation, and the Max Planck Institute. Accelerator Mass Spectrometry radiocarbon dating work was supported by the National Science Foundation (NSF) (BCS-1460369) to D.J.K. and B.J.C. D.R. was funded by NSF grant BCS-1032255, NIH (NIGMS) grant GM100233, the Paul M. Allen Frontiers Group, John Templeton Foundation grant 61220, a gift from Jean-Francois Clin, and the Howard Hughes Medical Institute. 该研究得到了国家自然科学基金“中国东南各族群的遗传混合”、国家社科基金重大项目“多学科视角下的南岛语族的起源和形成研究”、厦门大学南强青年拔尖人才支持计划A类、中央高校基本科研业务费等资助

Teachers know best: Preschoolers use sample size and diversity information in pedagogical, but not in non-pedagogical contexts.

Despite children’s early inductive sophistication (Gelman & Coley, 1991) they struggle to evaluate the composition of samples; before 8 years of age children do not recognize that diverse and large samples provide better evidence to make a prediction than non-diverse and small samples (Gutheil & Gelman, 1997). In this study we asked whether children’s awareness of the value of larger and more diverse samples is influenced by the source of the information presented to them. Preschoolers were presented samples of evidence about novel properties associated with different animals; half of items measured attention to sample size (e.g. two bears vs. five bears) and the other half measured attention to diversity (e.g. three brown bears vs. polar bear, brown bear, black bear). The samples were described as being provided by either “teachers” or “kids”. Participants were randomly assigned to one of three conditions. In the Induction condition participants were told a novel property about each of the samples (e.g. “These bears eat olin and these bears eat rooga”), and then asked to project one of the properties to a yet-to-be-seen animal (e.g., “Do you think this bear eats olin or rooga?”). In two other conditions children were told that two actors presented the samples (e.g. “This person says these animals eat olin and this person says these animals eat rooga”) and then asked to decide which actor they would trust to teach them about a novel animal. In the Teacher condition actors were described as “teachers”, and in the Child condition actors were described as “kids”. Our results indicate that children paid more attention to the composition of the samples presented by teachers than kids. In the Induction condition, children were not sensitive to sample size and diversity when making judgments, consistent with prior finding. However, children did consider these features when a teacher presented the information, but not when the same information was presented by a child. These results have implications for understanding the special status of reasoning in pedagogical contexts

Genetic Influences on Metabolite Levels: A Comparison across Metabolomic Platforms.

Metabolomic profiling is a powerful approach to characterize human metabolism and help understand common disease risk. Although multiple high-throughput technologies have been developed to assay the human metabolome, no technique is capable of capturing the entire human metabolism. Large-scale metabolomics data are being generated in multiple cohorts, but the datasets are typically profiled using different metabolomics platforms. Here, we compared analyses across two of the most frequently used metabolomic platforms, Biocrates and Metabolon, with the aim of assessing how complimentary metabolite profiles are across platforms. We profiled serum samples from 1,001 twins using both targeted (Biocrates, n = 160 metabolites) and non-targeted (Metabolon, n = 488 metabolites) mass spectrometry platforms. We compared metabolite distributions and performed genome-wide association analyses to identify shared genetic influences on metabolites across platforms. Comparison of 43 metabolites named for the same compound on both platforms indicated strong positive correlations, with few exceptions. Genome-wide association scans with high-throughput metabolic profiles were performed for each dataset and identified genetic variants at 7 loci associated with 16 unique metabolites on both platforms. The 16 metabolites showed consistent genetic associations and appear to be robustly measured across platforms. These included both metabolites named for the same compound across platforms as well as unique metabolites, of which 2 (nonanoylcarnitine (C9) [Biocrates]/Unknown metabolite X-13431 [Metabolon] and PC aa C28:1 [Biocrates]/1-stearoylglycerol [Metabolon]) are likely to represent the same or related biochemical entities. The results demonstrate the complementary nature of both platforms, and can be informative for future studies of comparative and integrative metabolomics analyses in samples profiled on different platforms