Characterizing the Epidemiological Transition in Mexico: National and Subnational Burden of Diseases, Injuries, and Risk Factors

Gretchen Stevens and colleagues estimate deaths and loss of healthy life years (measured in disability-adjusted life years, DALYs) for Mexico as a whole and its 32 states

A genome-wide association scan implicates DCHS2, RUNX2, GLI3, PAX1 and EDAR in human facial variation

We report a genome-wide association scan for facial features in B6,000 Latin Americans. We evaluated 14 traits on an ordinal scale and found significant association (P valueso5 10 8) at single-nucleotide polymorphisms (SNPs) in four genomic regions for three nose-related traits: columella inclination (4q31), nose bridge breadth (6p21) and nose wing breadth (7p13 and 20p11). In a subsample of B3,000 individuals we obtained quantitative traits related to 9 of the ordinal phenotypes and, also, a measure of nasion position. Quantitative analyses confirmed the ordinal-based associations, identified SNPs in 2q12 associated to chin protrusion, and replicated the reported association of nasion position with SNPs in PAX3. Strongest association in 2q12, 4q31, 6p21 and 7p13 was observed for SNPs in the EDAR, DCHS2, RUNX2 and GLI3 genes, respectively. Associated SNPs in 20p11 extend to PAX1. Consistent with the effect of EDAR on chin protrusion, we documented alterations of mandible length in mice with modified Edar funtion

Global, regional, and national under-5 mortality, adult mortality, age-specific mortality, and life expectancy, 1970–2016: a systematic analysis for the Global Burden of Disease Study 2016

BACKGROUND: Detailed assessments of mortality patterns, particularly age-specific mortality, represent a crucial input that enables health systems to target interventions to specific populations. Understanding how all-cause mortality has changed with respect to development status can identify exemplars for best practice. To accomplish this, the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) estimated age-specific and sex-specific all-cause mortality between 1970 and 2016 for 195 countries and territories and at the subnational level for the five countries with a population greater than 200 million in 2016. METHODS: We have evaluated how well civil registration systems captured deaths using a set of demographic methods called death distribution methods for adults and from consideration of survey and census data for children younger than 5 years. We generated an overall assessment of completeness of registration of deaths by dividing registered deaths in each location-year by our estimate of all-age deaths generated from our overall estimation process. For 163 locations, including subnational units in countries with a population greater than 200 million with complete vital registration (VR) systems, our estimates were largely driven by the observed data, with corrections for small fluctuations in numbers and estimation for recent years where there were lags in data reporting (lags were variable by location, generally between 1 year and 6 years). For other locations, we took advantage of different data sources available to measure under-5 mortality rates (U5MR) using complete birth histories, summary birth histories, and incomplete VR with adjustments; we measured adult mortality rate (the probability of death in individuals aged 15-60 years) using adjusted incomplete VR, sibling histories, and household death recall. We used the U5MR and adult mortality rate, together with crude death rate due to HIV in the GBD model life table system, to estimate age-specific and sex-specific death rates for each location-year. Using various international databases, we identified fatal discontinuities, which we defined as increases in the death rate of more than one death per million, resulting from conflict and terrorism, natural disasters, major transport or technological accidents, and a subset of epidemic infectious diseases; these were added to estimates in the relevant years. In 47 countries with an identified peak adult prevalence for HIV/AIDS of more than 0·5% and where VR systems were less than 65% complete, we informed our estimates of age-sex-specific mortality using the Estimation and Projection Package (EPP)-Spectrum model fitted to national HIV/AIDS prevalence surveys and antenatal clinic serosurveillance systems. We estimated stillbirths, early neonatal, late neonatal, and childhood mortality using both survey and VR data in spatiotemporal Gaussian process regression models. We estimated abridged life tables for all location-years using age-specific death rates. We grouped locations into development quintiles based on the Socio-demographic Index (SDI) and analysed mortality trends by quintile. Using spline regression, we estimated the expected mortality rate for each age-sex group as a function of SDI. We identified countries with higher life expectancy than expected by comparing observed life expectancy to anticipated life expectancy on the basis of development status alone. FINDINGS: Completeness in the registration of deaths increased from 28% in 1970 to a peak of 45% in 2013; completeness was lower after 2013 because of lags in reporting. Total deaths in children younger than 5 years decreased from 1970 to 2016, and slower decreases occurred at ages 5-24 years. By contrast, numbers of adult deaths increased in each 5-year age bracket above the age of 25 years. The distribution of annualised rates of change in age-specific mortality rate differed over the period 2000 to 2016 compared with earlier decades: increasing annualised rates of change were less frequent, although rising annualised rates of change still occurred in some locations, particularly for adolescent and younger adult age groups. Rates of stillbirths and under-5 mortality both decreased globally from 1970. Evidence for global convergence of death rates was mixed; although the absolute difference between age-standardised death rates narrowed between countries at the lowest and highest levels of SDI, the ratio of these death rates-a measure of relative inequality-increased slightly. There was a strong shift between 1970 and 2016 toward higher life expectancy, most noticeably at higher levels of SDI. Among countries with populations greater than 1 million in 2016, life expectancy at birth was highest for women in Japan, at 86·9 years (95% UI 86·7-87·2), and for men in Singapore, at 81·3 years (78·8-83·7) in 2016. Male life expectancy was generally lower than female life expectancy between 1970 and 2016, an

Global, regional, and national disability-adjusted life-years (DALYs) for 359 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017.

How long one lives, how many years of life are spent in good and poor health, and how the population's state of health and leading causes of disability change over time all have implications for policy, planning, and provision of services. We comparatively assessed the patterns and trends of healthy life expectancy (HALE), which quantifies the number of years of life expected to be lived in good health, and the complementary measure of disability-adjusted life-years (DALYs), a composite measure of disease burden capturing both premature mortality and prevalence and severity of ill health, for 359 diseases and injuries for 195 countries and territories over the past 28 years. Methods We used data for age-specific mortality rates, years of life lost (YLLs) due to premature mortality, and years lived with disability (YLDs) from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 to calculate HALE and DALYs from 1990 to 2017. We calculated HALE using age-specific mortality rates and YLDs per capita for each location, age, sex, and year. We calculated DALYs for 359 causes as the sum of YLLs and YLDs. We assessed how observed HALE and DALYs differed by country and sex from expected trends based on Socio-demographic Index (SDI). We also analysed HALE by decomposing years of life gained into years spent in good health and in poor health, between 1990 and 2017, and extra years lived by females compared with males. Findings Globally, from 1990 to 2017, life expectancy at birth increased by 7·4 years (95% uncertainty interval 7·1-7·8), from 65·6 years (65·3-65·8) in 1990 to 73·0 years (72·7-73·3) in 2017. The increase in years of life varied from 5·1 years (5·0-5·3) in high SDI countries to 12·0 years (11·3-12·8) in low SDI countries. Of the additional years of life expected at birth, 26·3% (20·1-33·1) were expected to be spent in poor health in high SDI countries compared with 11·7% (8·8-15·1) in low-middle SDI countries. HALE at birth increased by 6·3 years (5·9-6·7), from 57·0 years (54·6-59·1) in 1990 to 63·3 years (60·5-65·7) in 2017. The increase varied from 3·8 years (3·4-4·1) in high SDI countries to 10·5 years (9·8-11·2) in low SDI countries. Even larger variations in HALE than these were observed between countries, ranging from 1·0 year (0·4-1·7) in Saint Vincent and the Grenadines (62·4 years [59·9-64·7] in 1990 to 63·5 years [60·9-65·8] in 2017) to 23·7 years (21·9-25·6) in Eritrea (30·7 years [28·9-32·2] in 1990 to 54·4 years [51·5-57·1] in 2017). In most countries, the increase in HALE was smaller than the increase in overall life expectancy, indicating more years lived in poor health. In 180 of 195 countries and territories, females were expected to live longer than males in 2017, with extra years lived varying from 1·4 years (0·6-2·3) in Algeria to 11·9 years (10·9-12·9) in Ukraine. Of the extra years gained, the proportion spent in poor health varied largely across countries, with less than 20% of additional years spent in poor health in Bosnia and Herzegovina, Burundi, and Slovakia, whereas in Bahrain all the extra years were spent in poor health. In 2017, the highest estimate of HALE at birth was in Singapore for both females (75·8 years [72·4-78·7]) and males (72·6 years [69·8-75·0]) and the lowest estimates were in Central African Republic (47·0 years [43·7-50·2] for females and 42·8 years [40·1-45·6] for males). Globally, in 2017, the five leading causes of DALYs were neonatal disorders, ischaemic heart disease, stroke, lower respiratory infections, and chronic obstructive pulmonary disease. Between 1990 and 2017, age-standardised DALY rates decreased by 41·3% (38·8-43·5) for communicable diseases and by 49·8% (47·9-51·6) for neonatal disorders. For non-communicable diseases, global DALYs increased by 40·1% (36·8-43·0), although age-standardised DALY rates decreased by 18·1% (16·0-20·2)

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

Forouzanfar MH, Afshin A, Alexander LT, et al. Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015. LANCET. 2016;388(10053):1659-1724.Background The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors-the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57.8% (95% CI 56.6-58.8) of global deaths and 41.2% (39.8-42.8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211.8 million [192.7 million to 231.1 million] global DALYs), smoking (148.6 million [134.2 million to 163.1 million]), high fasting plasma glucose (143.1 million [125.1 million to 163.5 million]), high BMI (120.1 million [83.8 million to 158.4 million]), childhood undernutrition (113.3 million [103.9 million to 123.4 million]), ambient particulate matter (103.1 million [90.8 million to 115.1 million]), high total cholesterol (88.7 million [74.6 million to 105.7 million]), household air pollution (85.6 million [66.7 million to 106.1 million]), alcohol use (85.0 million [77.2 million to 93.0 million]), and diets high in sodium (83.0 million [49.3 million to 127.5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Copyright (C) The Author(s). Published by Elsevier Ltd

Global, regional, and national disability-adjusted life-years (DALYs) for 359 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017

How long one lives, how many years of life are spent in good and poor health, and how the population's state of health and leading causes of disability change over time all have implications for policy, planning, and provision of services. We comparatively assessed the patterns and trends of healthy life expectancy (HALE), which quantifies the number of years of life expected to be lived in good health, and the complementary measure of disability-adjusted life-years (DALYs), a composite measure of disease burden capturing both premature mortality and prevalence and severity of ill health, for 359 diseases and injuries for 195 countries and territories over the past 28 years.; We used data for age-specific mortality rates, years of life lost (YLLs) due to premature mortality, and years lived with disability (YLDs) from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 to calculate HALE and DALYs from 1990 to 2017. We calculated HALE using age-specific mortality rates and YLDs per capita for each location, age, sex, and year. We calculated DALYs for 359 causes as the sum of YLLs and YLDs. We assessed how observed HALE and DALYs differed by country and sex from expected trends based on Socio-demographic Index (SDI). We also analysed HALE by decomposing years of life gained into years spent in good health and in poor health, between 1990 and 2017, and extra years lived by females compared with males. Globally, from 1990 to 2017, life expectancy at birth increased by 7·4 years (95% uncertainty interval 7·1-7·8), from 65·6 years (65·3-65·8) in 1990 to 73·0 years (72·7-73·3) in 2017. The increase in years of life varied from 5·1 years (5·0-5·3) in high SDI countries to 12·0 years (11·3-12·8) in low SDI countries. Of the additional years of life expected at birth, 26·3% (20·1-33·1) were expected to be spent in poor health in high SDI countries compared with 11·7% (8·8-15·1) in low-middle SDI countries. HALE at birth increased by 6·3 years (5·9-6·7), from 57·0 years (54·6-59·1) in 1990 to 63·3 years (60·5-65·7) in 2017. The increase varied from 3·8 years (3·4-4·1) in high SDI countries to 10·5 years (9·8-11·2) in low SDI countries. Even larger variations in HALE than these were observed between countries, ranging from 1·0 year (0·4-1·7) in Saint Vincent and the Grenadines (62·4 years [59·9-64·7] in 1990 to 63·5 years [60·9-65·8] in 2017) to 23·7 years (21·9-25·6) in Eritrea (30·7 years [28·9-32·2] in 1990 to 54·4 years [51·5-57·1] in 2017). In most countries, the increase in HALE was smaller than the increase in overall life expectancy, indicating more years lived in poor health. In 180 of 195 countries and territories, females were expected to live longer than males in 2017, with extra years lived varying from 1·4 years (0·6-2·3) in Algeria to 11·9 years (10·9-12·9) in Ukraine. Of the extra years gained, the proportion spent in poor health varied largely across countries, with less than 20% of additional years spent in poor health in Bosnia and Herzegovina, Burundi, and Slovakia, whereas in Bahrain all the extra years were spent in poor health. In 2017, the highest estimate of HALE at birth was in Singapore for both females (75·8 years [72·4-78·7]) and males (72·6 years [69·8-75·0]) and the lowest estimates were in Central African Republic (47·0 years [43·7-50·2] for females and 42·8 years [40·1-45·6] for males). Globally, in 2017, the five leading causes of DALYs were neonatal disorders, ischaemic heart disease, stroke, lower respiratory infections, and chronic obstructive pulmonary disease. Between 1990 and 2017, age-standardised DALY rates decreased by 41·3% (38·8-43·5) for communicable diseases and by 49·8% (47·9-51·6) for neonatal disorders. For non-communicable diseases, global DALYs increased by 40·1% (36·8-43·0), although age-standardised DALY rates decreased by 18·1% (16·0-20·2). With increasing life expectancy in most countries, the question of whether the additional years of life gained are spent in good health or poor health has been increasingly relevant because of the potential policy implications, such as health-care provisions and extending retirement ages. In some locations, a large proportion of those additional years are spent in poor health. Large inequalities in HALE and disease burden exist across countries in different SDI quintiles and between sexes. The burden of disabling conditions has serious implications for health system planning and health-related expenditures. Despite the progress made in reducing the burden of communicable diseases and neonatal disorders in low SDI countries, the speed of this progress could be increased by scaling up proven interventions. The global trends among non-communicable diseases indicate that more effort is needed to maximise HALE, such as risk prevention and attention to upstream determinants of health

Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980-2017: a systematic analysis for the Global Burden of Disease Study 2017.

BACKGROUND: Global development goals increasingly rely on country-specific estimates for benchmarking a nation's progress. To meet this need, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 estimated global, regional, national, and, for selected locations, subnational cause-specific mortality beginning in the year 1980. Here we report an update to that study, making use of newly available data and improved methods. GBD 2017 provides a comprehensive assessment of cause-specific mortality for 282 causes in 195 countries and territories from 1980 to 2017. METHODS: The causes of death database is composed of vital registration (VR), verbal autopsy (VA), registry, survey, police, and surveillance data. GBD 2017 added ten VA studies, 127 country-years of VR data, 502 cancer-registry country-years, and an additional surveillance country-year. Expansions of the GBD cause of death hierarchy resulted in 18 additional causes estimated for GBD 2017. Newly available data led to subnational estimates for five additional countries-Ethiopia, Iran, New Zealand, Norway, and Russia. Deaths assigned International Classification of Diseases (ICD) codes for non-specific, implausible, or intermediate causes of death were reassigned to underlying causes by redistribution algorithms that were incorporated into uncertainty estimation. We used statistical modelling tools developed for GBD, including the Cause of Death Ensemble model (CODEm), to generate cause fractions and cause-specific death rates for each location, year, age, and sex. Instead of using UN estimates as in previous versions, GBD 2017 independently estimated population size and fertility rate for all locations. Years of life lost (YLLs) were then calculated as the sum of each death multiplied by the standard life expectancy at each age. All rates reported here are age-standardised

La inmunogenética más allá de la clínica: genes y patógenos que marcaron nuestra historia demográfica. 6 Cuarta época, año 2 (2018) septiembre-diciembre. Diario de Campo. Nombrar y contar. Visibilidad estadística de las poblaciones afromexicanas

Existe un número de condiciones clínicas asociadas con determinadas ancestrías, entre las cuales destaca la relación entre ciertos padecimientos autoinmunes y la ancestría nativa americana. Sin embargo, resulta lógico pensar que la presencia de estos padecimientos no fue seleccionada positivamente en el pasado y que las variantes relacionadas con estas afecciones fueron ventajosas en otro escenario. Los grupos nativos americanos tienen su origen en las poblaciones asiáticas. Tras dejar su continente de origen, viajaron a través de América y se encontraron con nuevos ambientes, animales y plantas, y por ello se expusieron a nuevos retos inmunes. La diversidad inicial en distintos genes se vio sometida a nuevas presiones selectivas al enfrentarse y adaptarse a una gran cantidad de microorganismos, muchos de los cuales posiblemente nunca habían enfrentado. Un caso particular de esta diversidad se aloja en los genes del sistema HLA, los cuales, a pesar de estar en proximidad, parecerían haber seguido historias evolutivas distintas. La pregunta obligada es: ¿la diversidad restringida en estos genes es el resultado de uno o más eventos adaptativos en América anteriores al siglo XVI, o somos testigos de uno de los más recientes ejemplos de selección natural en la historia de las poblaciones humanas?Acuña-Soto, Rodolfo et al. (2000). “Large epidemics of hemorrhagic fevers in Mexico 1545-1815”. The American Journal of Tropical Medicine and Hygiene, 62 (6), pp. 733-739._____ (2002). “Megadrought and megadeath in 16th century Mexico”. Emerging Infectious Diseases, 8 (4), pp. 360-362._____ (2004). “When half of the population died: The epidemic of hemorrhagic fevers of 1576 in Mexico”. FEMS Microbiology Letters, 240 (1), pp. 1-5.Barquera, Rodrigo (2012). “El papel de la genética de poblaciones en la inmunología del trasplante en México”. Gaceta Médica de México, 148 (1), pp. 52-67.Belich, Mônica P. et al. (1992). “Unusual HLA-B alleles in two tribes of Brazilian Indians”. Nature, 357 (6376), pp. 326-329.Bortolini, Maria Cátira, y Francisco M. Salzano (1996). “mtDNA diversity analysis in Amerindians and other human populations – how different are they?” Revista Brasileira de Genética, 19 (3), pp. 527-534.Bos, Kirsten I. et al. (2014). “Pre-Columbian mycobacterial genomes reveal seals as a source of New World human tuberculosis”. Nature, 514 (7523), pp. 494-497.Bothamley, Graham H. et al. (1989). “Association of uberculosis and M. tuberculosis-specific antibody levels with hla”. Journal of Infectious Diseases, 195 (3), pp. 549-555.Buckle, Geoffrey C. et al. (2012). “Typhoid fever and paratyphoid fever: Systematic review to estimate global morbidity and mortality for 2010”. Journal of Global Health, 2 (1), p. 10401.Callaway, Ewen (2016). “Plant and animal DNA suggests first Americans took the coastal route”. Nature, 536 (7615), p. 138.Chaaithanya, Itta Krishna et al. (2013). “HLA class II allele polymorphism in an outbreak of chikungunya fever in Middle Andaman, India”. Immunology, 140 (2), pp. 202-210.Conde-González, Carlos J. et al. (1993). “Historical account of venereal diseases in Mexico”. Genitourinary Medicine, 69 (6), pp. 462-466.Crosby, Alfred W. (1976). “Virgin soil epidemics as a factor in the aboriginal depopulation in America”. The William and Mary Quarterly, 33 (2), pp. 289-299.Delgado, Julio C. et al. (2006). “Aspartic acid homozygosity at codon 57 of HLA-DQ beta is associated with susceptibility to pulmonary tuberculosis in Cambodia”. The Journal of Immunology, 176 (2), pp. 1090-1097.Dunstan, Sarah J. et al. (2014). “Variation at HLA-DRB1 is associated with resistance to enteric fever”. Nature Genetics, 46 (12), pp. 1333-1336.Escamilla-Tilch, Mónica et al. (2013). “Association of genetic polymorphism of hla-drb1 antigens with the susceptibility to lepromatous leprosy”. Biomedical Reports, 1 (6), pp. 945-949.Goldfeld, Anne E. et al. (1998). “Association of an HLA-DQ allele with clinical tuberculosis”. Journal of the American Medical Association, 279 (3), pp. 226-228.González-Galarza, Faviel F. et al. (2015). “Allele frequency net 2015 update: New features for HLA epitopes, KIR and disease and HLA adverse drug reaction associations”. Nucleic Acids Research, 43, (núm. Especial de bases de datos), pp. D784-D788.Hammer, Christian et al. (2015). “Amino acid variation in HLA class II proteins is a major determinant of humoral response to common viruses”. The American Journal of Human Genetics, 97 (5), pp. 738-43.Hershberg, Ruth et al. (2008). “High functional diversity in Mycobacterium tuberculosis driven by genetic drift and human demography”. PLOS Biology, 6 (12), p. e311.Khomenko, A. G. et al. (1990). “Tuberculosis in patients with various HLA phenotypes”. Tubercle, 71 (3), pp. 187-192Krause-Kyora, Ben et al. (2018). “Ancient DNA study reveals HLA susceptibility locus for leprosy in medieval Europeans”. Nature Communications, 9 (1), p. 1569.Lindo, John et al. (2016). “A time transect of exomes from a Native American population before and after European contact”. Nature Communications, 7, p. 13175.López Herráez, David et al. (2013). “Rheumatoid arthritis in Latin Americans enriched for Amerindian ancestry is associated with loci in chromosomes 1, 12, and 13, and the HLA class II region”. Arthritis and Rheumatology, 65 (6), pp. 1457-1467.Lutz, Charles T. (2014). “HLA BW4 and BW6 epitopes recognized by antibodies and Natural Killer cells”. Current Opinion in Organ Transplantation, 18 (4), pp. 436-441.Marr, John S., y James B. Kiracofe (2000). “Was the huey cocoliztli a haemorrhagic fever?”. Medical History, 44 (3), pp. 341-362.Monack, Denise M. et al. (2004). “Persistent bacterial infections: The interface of the pathogen and the host immune system”. Nature Reviews Microbiology, 2 (9), pp. 747-765.Moreno-Estrada, Andrés et al. (2014). “The genetics of Mexico recapitulates Native American substructure and affects biomedical traits”. Science, 344 (6189), pp. 1280-1285.Palafox, Damián et al. (2016). “Determinación de HLA en pacientes con Síndrome de Parry Romberg atendidos en el Servicio de Cirugía Plástica y Reconstructiva del Hospital General ‘Dr. Manuel Gea González’”. Cirugía Plástica Ibero-Latinoamericana, 42 (2), pp. 115-120.Parham, P. et al. (1997). “Episodic evolution and turnover of HLA-B in the indigenous human populations of the Americas. Tissue Antigens, 50 (3), pp. 219-232.Pedersen, Mikkel W. et al. (2016). “Postglacial viability and colonization in North America’s ice-free corridor”. Nature, 537 (7618), pp. 45-49.Peschken, Christine A., y John M. Esdaile (1999). “Rheumatic diseases in North America’s indigenous peoples”. Seminars in Arthritis and Rheumatism, 28 (6), pp. 368-391.Pons-Estel, Bernardo A. et al. (2004). “The GLADEL multinational Latin American prospective inception cohort of 1,214 patients with systemic lupus erythematosus: ethnic and disease heterogeneity among ‘Hispanics’”. Medicine, 83 (1), pp. 1-17.Ramírez Gómez, L. A. et al. (2008). “Childhood systemic lupus erythematosus in Latin America. The GLADEL experience in 230 children”. Lupus, 17 (6), pp. 596-604.Salo, Wilmar L. et al. (1994). “Identification of Mycobacterium tuberculosis DNA in a pre-Columbian Peruvian mummy”. Proceedings of the National Academy of Sciences of the United States of America, 91 (6), pp. 2091-2094.Salomé, Jenny von et al. (2007). “Full-length sequence analysis of the HLA-DRB1 locus suggests a recent origin of alleles”. Immunogenetics, 59 (4), pp. 261-271.Salzano, Francisco M. (2002). “Molecular variability in Amerindians: Widespread but uneven information”. Anais da Academia Brasileira de Ciências, 74 (2), pp. 223-263.Sanchez, Elena et al. (2010). “Genetically determined Amerindian ancestry correlates with increased frequency of risk alleles for systemic lupus erythematosus”. Arthritis and Rheumatology, 62 (12), pp. 3722-3729.Sanchez, Elena et al. (2010). “Genetically determined Amerindian ancestry correlates with increased frequency of risk alleles for systemic lupus erythematosus”. Arthritis and Rheumatology, 62 (12), pp. 3722-3729.Sanchez, Elena et al. (2010). “Genetically determined Amerindian ancestry correlates with increased frequency of risk alleles for systemic lupus erythematosus”. Arthritis and Rheumatology, 62 (12), pp. 3722-3729.Sanchez, Elena et al. (2010). “Genetically determined Amerindian ancestry correlates with increased frequency of risk alleles for systemic lupus erythematosus”. Arthritis and Rheumatology, 62 (12), pp. 3722-3729.Sanchez, Elena et al. (2010). “Genetically determined Amerindian ancestry correlates with increased frequency of risk alleles for systemic lupus erythematosus”. Arthritis and Rheumatology, 62 (12), pp. 3722-3729.Single, Richard M. et al. (2007). “Global diversity and evidence for coevolution of KIR and HLA. Nature Genetics, 39 (9), pp. 1114-1119.Somolinos d’Ardois, Germán (1956 / 2015). “El manuscrito sobre el cocoliztli”. En Francisco Hernández [Obras completas, t. IV] pp. 475-480. México: UNAM.Spyrou, Maria A. et al. (2019). “Ancient pathogen genomics as an emerging tool for infectious disease research”. Nature Reviews Genetics, 20, pp. 323-340.Tamm, Erika et al. (2007). “Beringian standstill and spread of Native American founders”. PLoS One, 2(9), p. e829.Terán-Escandón, David et al. (1999) “Human leukocyte antigen-associated susceptibility to pulmonary tuberculosis: Molecular analysis of class II alleles by DNA amplification and oligonucleotide hybridization in Mexican patients. Chest, 115 (2), pp. 428-433.Terán-Escandón, David et al. (1999) “Human leukocyte antigen-associated susceptibility to pulmonary tuberculosis: Molecular analysis of class II alleles by DNA amplification and oligonucleotide hybridization in Mexican patients. Chest, 115 (2), pp. 428-433.Thornton, Russell (1997). “Aboriginal North American population and rates of decline, ca. a.d. 1500-1901”. Current Anthropology, 38, pp. 310-315.Vågene, Åshild J. et al. (2018). “Salmonella enterica genomes from victims of a major sixteenth-century epidemic in Mexico”. Nature Ecology and Evolution, 2 (3), pp. 520-528.Wang, Sijia et al. (2007). “Genetic variation and population structure in Native Americans”. PLOS Genetics, 3 (11), p. e185.Watkins, David I. et al. (1992). “New recombinant HLA-B alleles in a tribe of South American Amerindians indicate rapid evolution of MHC class I loci”. Nature, 357 (6376), pp. 329-333.Wirth, Thierry et al. (2008). “Origin, spread and demography of the Mycobacterium tuberculosis complex”. PLOS Pathogens, 4 (9), p. e1000160.Zhou, Zhemin et al. (2017). “Millennia of genomic stability within the invasive Para C lineage of Salmonella enterica”. Recuperado de https://www.biorxiv.org/content/early/2017/02/14/10575

Una última entrevista: el seguimiento molecular a una pieza ósea de un contexto prehispánico. 6 Cuarta época, año 2 (2018) septiembre-diciembre. Diario de Campo. Nombrar y contar. Visibilidad estadística de las poblaciones afromexicanas

Con la intención de acercar a todos los actores y espectadores a las transformaciones que sufre un fragmento óseo, desde su salida del microambiente en su contexto arqueológico hasta convertirse en parte de la discusión de un artículo o libro publicado, en esta sección el autor se dio a la tarea de realizar un seguimiento a través de todos los pasos analíticos, complementando con material fotográfico para hacer accesible la experiencia del DNA antiguo más allá de los artículos y reportes al público en general, esto con el fin de exponer el trayecto que une a la pieza ósea con su participación en la discusión científica.Allentof, Morten E. et al. (2015). “Population genomics of Bronze Age Eurasia”. Nature, 522, pp. 167-172.Brandini, Stefania et al. (2018). “The Paleo-Indian entry into South America according to mitogenomes”. Molecular Biology Evolution, 35, pp. 299-311.Briggs, Adrian W. et al. (2010). “Removal of deaminated cytosines and detection of in vivo methylation in ancient DNA”. Nucleic Acids Research, 38, p: e87.Higuchi, Russell et al. (1984). “DNA sequences from the quagga, an extinct member of the horse family”. Nature, 312, pp. 282-4.Hofreiter, Michael et al. (2001). “DNA sequences from multiple amplifications reveal artifacts induced by cytosine deamination in ancient DNA”. Nucleic Acids Research, 29, pp. 4793-4799.Hotchner, Aaron (1966). Papa Hemingway: A personal memoir. Nueva York: Random House.Márquez Morfín, Lourdes (2010). “Morir por los dioses… y uno que otro humano. Sacrificio de niños en Chichen Itzá o práctica funeraria”. En Lourdes Márquez Morfín. Los niños, actores sociales ignorados. Levantando el velo, una mirada al pasado (pp. 253-282). México: ENAH-INAH / Conaculta / PROMEP.Meyer, Matthias, y Kircher, Martin (2010). “Illumina sequencing library preparation for highly multiplexed target capture and sequencing”. Cold Spring Harbor Protocols, 2010 (6): prot5448. doi:10.1101/pdb. prot5448.Pääbo, Svante (1985a). “Preservation of DNA in ancient Egyptian mummies”. J Arch Sci, 12, pp. 411-417._____ (1985b). “Molecular cloning of Ancient Egyptian mummy DNA. Nature, 314, pp. 644-645Pinhasi, Ron et al. (2015), “Optimal ancient DNA yields from the inner ear part of the human petrous bone”. PLoS One, 10, p. e0129102.Saint Pierre, Michelle de et al. (2012). “An alternative model for the early peopling of southern South America revealed by analyses of three mitochondrial DNA haplogroups”. PLoS One, 7, p. e43486

Estudo de HLA classes I e II em trinta pacientes equatorianos com artrite reumatoide em comparação com alelos de indivíduos sadios e afetados com outras doenças reumáticas

INTRODUÇÃO: A artrite reumatoide (AR) é uma doença inflamatória crônica sistêmica autoimune que provém de uma desordem incapacitante. Até hoje, a etiologia da AR é desconhecida. No entanto, já se cogitou a existência de indivíduos geneticamente passíveis de tê-la. Muitos estudos já foram realizados em todo o mundo, como, por exemplo, na Polônia, Argentina, Chile, México, Brasil, Colômbia, entre outros países, com relação à influência entre os alelos HLA-DR e a doença, mas não no Equador. OBJETIVO: O principal objetivo deste estudo foi determinar a participação dos alelos de HLA classes I e II em pacientes com AR. PACIENTES E MÉTODOS: Esta pesquisa foi desenvolvida em 30 pacientes adultos com AR, previamente diagnosticados de acordo com os critérios de classificação do Colégio Norte-Americano de Reumatologia (ACR, 1987) e 28 controles. Para a tipificação de HLA classes I e II, adotou-se a técnica PCR-SSP, e as significâncias estatísticas foram avaliadas pelo teste de Qui-Quadrado. RESULTADOS: O HLA-DR4 está presente em 76,7% dos pacientes, com uma frequência alélica de 45%, enquanto apenas 21% dos sujeitos controle o apresentaram. O teste de Qui-Quadrado confirma que as variáveis HLA-DR4 e RA estão altamente vinculadas (X² = 11,38, P = 0,00074). CONCLUSÃO: Há frequência maior de HLA-DR4 e HLA-DR14. Os resultados encontrados são similares aos encontrados em outros estudos. Porém, seria desejável aumentar o tamanho da amostra para encontrar um maior número de perfis genéticos e de alelos envolvidos