The genomic landscape of Mexican Indigenous populations brings insights into the peopling of the Americas.

The genetic makeup of Indigenous populations inhabiting Mexico has been strongly influenced by geography and demographic history. Here, we perform a genome-wide analysis of 716 newly genotyped individuals from 60 of the 68 recognized ethnic groups in Mexico. We show that the genetic structure of these populations is strongly influenced by geography, and our demographic reconstructions suggest a decline in the population size of all tested populations in the last 15-30 generations. We find evidence that Aridoamerican and Mesoamerican populations diverged roughly 4-9.9 ka, around the time when sedentary farming started in Mesoamerica. Comparisons with ancient genomes indicate that the Upward Sun River 1 (USR1) individual is an outgroup to Mexican/South American Indigenous populations, whereas Anzick-1 was more closely related to Mesoamerican/South American populations than to those from Aridoamerica, showing an even more complex history of divergence than recognized so far.

Population level comparisons in central Mexico using cranial nonmetric traits.

OBJECTIVES: We study the genetic diversity between Classic Teotihuacan and its neighboring towns trying to understand how far or close they are at the genetic level. MATERIALS AND METHODS: We use cranial nonmetric traits to study a sample of 280 adult skulls from archaeological sites running from the late Preclassic to the early Postclassic. Samples of Classic Teotihuacan were studied for La Ventilla and San Sebastián Xolalpan neighbors. For the Epiclassic period, samples from Xaltocan, Toluca valley, Mogotes and Xico were used. For the Preclassic and Postclassic samples from Xico were also used. We used a parametric bootstrap for the mean measure of divergence for the statistical analysis. RESULTS: Samples from Xico have small biodistance from Preclassic to Postclassic. Samples from Los Mogotes differ depending on the functional context of deposition, with individuals from household burials (funerary) differing from non-funerary, ceremonial interments and exhibiting affinities to Epiclassic samples from Toluca valley. Epiclassic populations from Xaltocan vary significantly from any samples analyzed. Samples from Classic period Teotihuacan vary considerably among them but form a separate genetic group from all the other populations under study. CONCLUSIONS: The great biodistance separation among Classic Teotihuacan and its neighbor villages of central Mexico let us conclude that, contrary from the classical idea that those villages were confirmed by the inhabitants of Teotihuacan's collapse: They indeed remain as separate populations by themselves.

Importance of the geographic barriers to promote gene drift and avoid pre- and post-Columbian gene flow in Mexican native groups: Evidence from forensic STR Loci.

OBJECTIVE: To analyze the origin, structure, relationships, and recent admixture in Mexican Native groups based on 15 STRs commonly used in human identification. METHODS: We analyzed 39 Mexican Native population samples using STR databases based on the AmpFlSTR® Identifiler kit (n = 3,135), including Mexican-Mestizos (admixed), European and African populations, as reference. RESULTS: Based upon effective population size (Ne) differences, Native groups were clustered into three regions: i) Center-Southeast groups, characterized by larger Ne, migration rate (Nm), genetic diversity (He), and relative homogeneity principally in the Yucatan Peninsula; ii) Isolated southern groups from Chiapas and Oaxaca, characterized by lower Ne, Nm, and He (i.e. higher isolation and genetic differentiation); iii) North-Northwest groups, which are similar to the previous group but are characterized by generating the widest gene flow barrier in the Pre-Hispanic Mexican territory, and currently by elevated admixture in some northern Native groups. Despite the relative congruence between genetic relationships with cultural, linguistic, geographic criteria, these factors do not explain the present-day population structure of Native groups, excepting in those linguistically related to the Mayan that show higher homogeneity. The Isolation by distance model was demonstrated at long distances (>1,500 km), whereas geographic isolation stands as a determining factor to avoid both non-indigenous admixture and bottleneck processes. CONCLUSIONS: Different dynamics of gene flow and drift were observed among Mexican Native groups, highlighting the geographic barriers (mountains, canyons and jungle regions) as the main factor differentiating Pre-Hispanic populations, and eventually helping to avoid Post-European contact admixture and population bottleneck. Am J Phys Anthropol 160:298-316, 2016. © 2016 Wiley Periodicals, Inc.

Best Practices for Effective Clinical Partnerships with Indigenous Populations of North America (American Indian, Alaska Native, First Nations, Métis, and Inuit).

This article presents a review of the literature to identify best practices for clinical partnerships with indigenous populations of North America, specifically American Indian/Alaska Native, First Nations, Métis, and Inuit of Canada. The authors have identified best practices and lessons learned from collaborating with indigenous populations, presented in 2 categories: conceptual guidelines and health care delivery guidelines. Major themes include the importance of trust and communication, the delivery of culturally congruent health care, and the necessity of working in partnership with tribal entities for successful delivery of health care. Best practices in health care delivery with indigenous populations are presented.

One little, too little: Counting Canada's indigenous people for improved health reporting.

The way state governments, worldwide, count or do not count Indigenous peoples has contributed to inconsistent reporting of Indigenous health statistics. To address unreliable reporting in Canada, we reviewed laws on Indian status and the development of a national Indian Registration System (IRS) to track Indian status and eligibility. With this information as a guide, we linked the IRS to the Manitoba provincial health registry systems and were able to identify individuals with Indian status for health reporting. To improve reporting, we identified individuals often missed in this type of linkage. For instance, we identified children and adult children who were eligible for Indian status but not yet registered. Equally as important, we identified individuals not eligible for Indian status but have Indian heritage and/or represent potential individual Indian status eligibility cases before the courts to right a historic form of identity sex discrimination that has made them invisible in Canadian society and health reporting. A familial kinship approach was used to identify Indian children and adult children typically missed when a strict legal entitlement criteria is used for data linkage. Our reflective socio-legal data linkage approach expanded the number of Indian peoples for health reporting purposes and demonstrated a feasible, inclusive way to report on the health of Indians in Canada.

Self-reported versus administrative identification of American Indian and Alaska Native arrestees: effects on relative estimates of illicit drug use and alcohol abuse.

Arrestee Drug Abuse Monitoring program data were used to consider the effects of two methods of racial classification upon estimates of illicit drug use and alcohol abuse among American Indian/Alaska Native (AI/AN) arrestees. Overall, compared to arrestees who self-identified as Black, White, Asian/Pacific Islander, or Hispanic, arrestees self-identifying as AI/AN were most likely to be identified administratively as something other than AI/AN. Results of 'difference of difference' analyses indicate that differences in estimates of AI/AN versus non-AI/AN arrestees' illicit drug use and alcohol abuse were much more extreme when identification was based on administrative records than when based upon arrestees' self-reports.

Racial misclassification of American Indians and Alaska Natives by Indian Health Service Contract Health Service Delivery Area.

OBJECTIVES: We evaluated the racial misclassification of American Indians and Alaska Natives (AI/ANs) in cancer incidence and all-cause mortality data by Indian Health Service (IHS) Contract Health Service Delivery Area (CHSDA). METHODS: We evaluated data from 3 sources: IHS-National Vital Statistics System (NVSS), IHS-National Program of Cancer Registries (NPCR)/Surveillance, Epidemiology and End Results (SEER) program, and National Longitudinal Mortality Study (NLMS). We calculated, within each data source, the sensitivity and classification ratios by sex, IHS region, and urban-rural classification by CHSDA county. RESULTS: Sensitivity was significantly greater in CHSDA counties (IHS-NVSS: 83.6%; IHS-NPCR/SEER: 77.6%; NLMS: 68.8%) than non-CHSDA counties (IHS-NVSS: 54.8%; IHS-NPCR/SEER: 39.0%; NLMS: 28.3%). Classification ratios indicated less misclassification in CHSDA counties (IHS-NVSS: 1.20%; IHS-NPCR/SEER: 1.29%; NLMS: 1.18%) than non-CHSDA counties (IHS-NVSS: 1.82%; IHS-NPCR/SEER: 2.56%; NLMS: 1.81%). Race misclassification was less in rural counties and in regions with the greatest concentrations of AI/AN persons (Alaska, Southwest, and Northern Plains). CONCLUSIONS: Limiting presentation and analysis to CHSDA counties helped mitigate the effects of race misclassification of AI/AN persons, although a portion of the population was excluded.

Blood politics, ethnic identity, and racial misclassification among American Indians and Alaska Natives.

Misclassification of race in medical and mortality records has long been documented as an issue in American Indian/Alaska Native data. Yet, little has been shared in a cohesive narrative which outlines why misclassification of American Indian/Alaska Native identity occurs. The purpose of this paper is to provide a summary of the current state of the science in racial misclassification among American Indians and Alaska Natives. We also provide a historical context on the importance of this problem and describe the ongoing political processes that both affect racial misclassification and contribute to the context of American Indian and Alaska Native identity.

Upper Palaeolithic Siberian genome reveals dual ancestry of Native Americans.

The origins of the First Americans remain contentious. Although Native Americans seem to be genetically most closely related to east Asians, there is no consensus with regard to which specific Old World populations they are closest to. Here we sequence the draft genome of an approximately 24,000-year-old individual (MA-1), from Mal'ta in south-central Siberia, to an average depth of 1×. To our knowledge this is the oldest anatomically modern human genome reported to date. The MA-1 mitochondrial genome belongs to haplogroup U, which has also been found at high frequency among Upper Palaeolithic and Mesolithic European hunter-gatherers, and the Y chromosome of MA-1 is basal to modern-day western Eurasians and near the root of most Native American lineages. Similarly, we find autosomal evidence that MA-1 is basal to modern-day western Eurasians and genetically closely related to modern-day Native Americans, with no close affinity to east Asians. This suggests that populations related to contemporary western Eurasians had a more north-easterly distribution 24,000 years ago than commonly thought. Furthermore, we estimate that 14 to 38% of Native American ancestry may originate through gene flow from this ancient population. This is likely to have occurred after the divergence of Native American ancestors from east Asian ancestors, but before the diversification of Native American populations in the New World. Gene flow from the MA-1 lineage into Native American ancestors could explain why several crania from the First Americans have been reported as bearing morphological characteristics that do not resemble those of east Asians. Sequencing of another south-central Siberian, Afontova Gora-2 dating to approximately 17,000 years ago, revealed similar autosomal genetic signatures as MA-1, suggesting that the region was continuously occupied by humans throughout the Last Glacial Maximum. Our findings reveal that western Eurasian genetic signatures in modern-day Native Americans derive not only from post-Columbian admixture, as commonly thought, but also from a mixed ancestry of the First Americans.

Phylogeny of the southern Plateau: an osteometric evaluation of inter-tribal relations.

This project focuses on whether determination of physical differences among closely affiliated Native American populations inhabiting the southern Plateau is possible. The study includes 318 individuals and approximately 100 recorded measurements of the cranium, humerus, femur, and tibia of each individual. The compiled measurements were evaluated in terms of their implied genetic affiliation, environmental location, and cultural identity. Along with metric measurements, pathological conditions were also compared to provide a control experiment to confirm or reject the findings. The results indicate that there are slight differences detectable among the populations as a result of environmental and European contact factors. The most apparent disparities are seen in relation to the size and shape of the lower extremities, which are highly associated with environmental and dietary stress. Pathological analysis supports the findings of the osteological analysis, suggesting that if the location of the burial and a general time period for interment are known, cultural identification is possible.

Genetic structure of three Native Mexican communities based on mtDNA haplogroups, and ABO and Rh blood group systems.

OBJECTIVE: The goals of this population genetics study were to describe mtDNA haplogroups and ABO and Rh blood group systems of 3 Native Mexican populations, to determine their genetic variability, and to compare their haplogroups with those of 13 Native Mexican populations previously reported. MATERIAL AND METHODS: The three communities under analysis were a Tepehua-speaking community from Huehuetla (Hidalgo state), an Otomi-speaking community from San Antonio el Grande (Hidalgo state), and a Zapotec-speaking community from Juchitán (Oaxaca state). Every subject studied in each community had four grandparents who were born in the same community and spoke the same language. The four Amerindian mtDNA haplogroups (A, B, C and D) were studied by restriction analysis and gel electrophoresis. RESULTS: Regarding the blood groups, the O group was the most frequent in the three populations (97.2, 94.7, and 86.2%, respectively), as well as the Rh+ group (100, 100, 84%). The three populations analyzed were in Hardy-Weinberg equilibrium. In respect to the mtDNA haplogroups, A, B, C and D, their percentage was 33.3, 36.1, 13.9 and 5.6 % in Huehuetla; 39.5, 13.2, 39.5 and 2.6 % in San Antonio el Grande, and 55.3, 21.0, 7.9 and 5.2 % in Juchitán. Between 5 and 11% of the haplogroups were of non-Amerindian origin, probably due to admixture with Caucasian and African populations, as has been reported in the past. No statistically-significant differences were found among the three populations studied or between them and 13 previously reported Native Mexican populations.

Including self-reported race to improve cancer surveillance data for American Indians and Alaska Natives in Washington state.

BACKGROUND: American Indians and Alaska Natives (AI/AN) are frequently misclassified as another race in cancer surveillance systems, resulting in underestimated morbidity and mortality. Linkage methods with administrative records have been used to correct AI/AN misclassification, but AI/AN populations living in urban areas, and those who self-identify as AI/AN race, continue to be under-ascertained. The aim of this study was to evaluate racial misclassification in two cancer registries in Washington State using an urban AI/AN patient roster linked with a list of Indian Health Service (IHS) enrollees. METHODS: We conducted probabilistic record linkages to identify racial misclassification using a combined demographic dataset of self-identified AI/AN patients of a large, urban Indian health center, and administratively-identified AI/AN enrolled with the IHS. Age-adjusted incidence rates were calculated for 3 linkage populations: AI/ AN originally coded in each cancer registry, post-linkage AI/AN identified through the IHS roster alone, and post-linkage AI/AN identified through either the urban or IHS file. RESULTS: In the state and regional cancer registries, 11% and 18%, respectively, of matched cases were originally coded as a race other than AI/AN; approximately 35% of these were identified by the urban file alone. Incidence rate estimates increased after linkage with the IHS file, and further increased with the addition of urban records. Matches identified by the urban patient file resulted in the largest relative incidence change being demonstrated for King County (which includes Seattle); the all-site invasive cancer rate increased 8.8%, from 443 to 482 per 100,000. CONCLUSIONS: Inclusion of urban and self-identified AI/AN records can increase case ascertainment in cancer surveillance systems beyond linkage methods using only administrative sources.

Misclassification of American Indian race in state cancer data among non-federally recognized Indians in North Carolina.

BACKGROUND: Equitable distribution of health care resources relies on accurate morbidity and mortality data, classified by race. Accurate classification is a problem, particularly for non-federally recognized American Indians (AI) receiving care outside of the Indian Health Service. METHODS: We identified counties in North Carolina that had the majority of AIs belonging to the 7 state-recognized, non-federally recognized tribes. We collaborated with the tribe in each county and compared the incident cases of cancer in the North Carolina Central Cancer Registry (NCCCR) to the tribal rolls. Data were analyzed to calculate what percent of names on both lists were not correctly identified as AI in the NCCCR. We corrected the NCCCR classification and calculated the percentage misclassified, then recalculated the cancer incidence rates for 4 major cancers (prostate, female breast, lung, and colorectal). We compared the recalculated rate to the original rate. RESULTS: There were 626 AIs on the tribal rolls; 112 (17.9%) were not identified as AI on the NCCCR list. Comparing 1996-2000 age-adjusted cancer incidence rates before and after reclassification, the increase in rates were prostate 41%, female breast 18%, lung 10%, and 11% for colorectal cancers. There was less than a 2% increase in cancer rates for the combined 4 sites for Blacks and Whites, before and after reclassification, and 19% for AIs. CONCLUSIONS: The study estimated 18% misclassification of non-federally recognized AIs in cancer registration in North Carolina, and determined an underestimation of cancer rates in the population. The underestimation of cancer burden among AIs in North Carolina may affect resources allocated for prevention, screening, and treatment programs, as well as funding for research.

Tribal linkage and race data quality for American Indians in a state cancer registry.

BACKGROUND: Racial misclassification of American Indian and Alaska Native (AI/AN) individuals as non-AI/AN in cancer registries presents problems for cancer surveillance, research, and public health practice. The aim of this study was to investigate the efficiency of tribal linkages in enhancing the quality of racial information in state cancer registries. METHODS: Registry Plus Link Plus 2.0 probabilistic record linkage software was used to link the Michigan state cancer registry data (1985-2004; 1,031,168 cancer cases) to the tribal membership roster (40,340 individuals) in July of 2007. A data set was created containing AI/AN cancer cases identified by the state registry, Indian Health Service (IHS) linkages, and tribal linkage. The differences between these three groups of individuals were compared by distribution of demographic, diagnostic, and county-level characteristics using multilevel analysis (conducted in 2007-2008). RESULTS: From 1995 to 2004, the tribal enrollment file showed linkages to 670 cancer cases (583 individuals) and the tribal linkage led to the identification of 190 AI/AN cancer cases (168 individuals) that were classified as non-AI/AN in the registry. More than 80% of tribal members were reported as non-AI/AN to the registry. Individuals identified by IHS or tribal linkages were different from those reported to be AI/AN in terms of stage at diagnosis, tumor confirmation, and characteristics of the county of diagnosis, including contract health services availability, tribal health services availability, and proportion of AI/AN residents. CONCLUSIONS: The data linkage between tribal and state cancer registry data sets improved racial classification validity of AI/AN Michigan cancer cases. Assessing tribal linkages is a simple, noninvasive way to improve the accuracy of state cancer data for AI/AN populations and to generate tribe-specific cancer information.

Effect of race and ethnicity classification on survey estimates: Anomaly of the weighted totals of American Indians and Alaska Natives.

Racial classification is a paramount concern in data collection and analysis for American Indians and Alaska Natives (AI/ANs) and has far-reaching implications in health research. We examine how different racial classifications affect survey weights and consequently change health-related indicators for the AI/AN population in California. Using a very large random population-based sample of AI/ANs, we compared the impact of three weighting strategies on counts and rates of selected health indicators. We found that different weights examined in this study did not change the percentage estimates of health-related variables for AI/ANs, but did influence the population total estimates dramatically. In survey data, different racial classifications and tabulations of AI/ANs could yield discrepancies in weighted estimates for the AI/AN population. Policy makers need to be aware that the choice of racial classification schemes for this racial-political group can generally influence the data they use for decision making.

Distribution of Y chromosomes among native North Americans: a study of Athapaskan population history.

In this study, 231 Y chromosomes from 12 populations were typed for four diagnostic single nucleotide polymorphisms (SNPs) to determine haplogroup membership and 43 Y chromosomes from three of these populations were typed for eight short tandem repeats (STRs) to determine haplotypes. These data were combined with previously published data, amounting to 724 Y chromosomes from 26 populations in North America, and analyzed to investigate the geographic distribution of Y chromosomes among native North Americans and to test the Southern Athapaskan migration hypothesis. The results suggest that European admixture has significantly altered the distribution of Y chromosomes in North America and because of this caution should be taken when inferring prehistoric population events in North America using Y chromosome data alone. However, consistent with studies of other genetic systems, we are still able to identify close relationships among Y chromosomes in Athapaskans from the Subarctic and the Southwest, suggesting that a small number of proto-Apachean migrants from the Subarctic founded the Southwest Athapaskan populations.

Using "socially assigned race" to probe white advantages in health status.

OBJECTIVES: We explore the relationships between socially assigned race ("How do other people usually classify you in this country?"), self-identified race/ethnicity, and excellent or very good general health status. We then take advantage of subgroups which are discordant on self-identified race/ethnicity and socially assigned race to examine whether being classified by others as White conveys an advantage in health status, even for those who do not self-identify as White. METHODS: Analyses were conducted using pooled data from the eight states that used the Reactions to Race module of the 2004 Behavioral Risk Factor Surveillance System. RESULTS: The agreement of socially assigned race with self-identified race/ethnicity varied across the racial/ethnic groups currently defined by the United States government. Included among those usually classified by others as White were 26.8% of those who self-identified as Hispanic, 47.6% of those who self-identified as American Indian, and 59.5% of those who self-identified with More than one race. Among those who self-identified as Hispanic, the age-, education-, and language-adjusted proportion reporting excellent or very good health was 8.7 percentage points higher for those socially assigned as White than for those socially assigned as Hispanic (P=.04); among those who self-identified as American Indian, that proportion was 15.4 percentage points higher for those socially assigned as White than for those socially assigned as American Indian (P=.05); and among those who self-identified with More than one race, that proportion was 23.6 percentage points higher for those socially assigned as White than for those socially assigned as Black (P<.01). On the other hand, no significant differences were found between those socially assigned as White who self-identified as White and those socially assigned as White who self-identified as Hispanic, as American Indian, or with More than one race. CONCLUSIONS: Being classified by others as White is associated with large and statistically significant advantages in health status, no matter how one self-identifies.