Gestational Diabetes Mellitus Subtypes Classified by Oral Glucose Tolerance Test and Maternal and Perinatal Outcomes: Results of a Mexican Multicenter Prospective Cohort Study "Cuido Mi Embarazo".

Purpose: This study explores the impact of gestational diabetes mellitus (GDM) subtypes classified by oral glucose tolerance test (OGTT) values on maternal and perinatal outcomes. Patients and Methods: This multicenter prospective cohort study (May 2019-December 2022) included participants from the Mexican multicenter cohort study Cuido mi Embarazo (CME). Women were classified into four groups per 75-g 2-h OGTT: 1) normal glucose tolerance (normal OGTT), 2) GDM-Sensitivity (isolated abnormal fasting or abnormal fasting in combination with 1-h or 2-h abnormal results), 3) GDM-Secretion (isolated abnormal values at 1-h or 2-h or their combination), and 4) GDM-Mixed (three abnormal values). Cesarean delivery, neonates large for gestational age (LGA), and pre-term birth rates were among the outcomes compared. Between-group comparisons were analyzed using either the t-test, chi-square test, or Fisher's exact test. Results: Of 2,056 Mexican pregnant women in the CME cohort, 294 (14.3%) had GDM; 53.7%, 34.4%, and 11.9% were classified as GDM-Sensitivity, GDM-Secretion, and GDM-Mixed subtypes, respectively. Women with GDM were older (p = 0.0001) and more often multiparous (p = 0.119) vs without GDM. Cesarean delivery (63.3%; p = 0.02) and neonate LGA (10.7%; p = 0.078) were higher in the GDM-Mixed group than the overall GDM group (55.6% and 8.4%, respectively). Pre-term birth was more common in the GDM-Sensitivity group than in the overall GDM group (10.2% vs 8.5%, respectively; p=0.022). At 6 months postpartum, prediabetes was more frequent in the GDM-Sensitivity group than in the overall GDM group (31.6% vs 25.5%). Type 2 diabetes was more common in the GDM-Mixed group than in the overall GDM group (10.0% vs 3.3%). Conclusion: GDM subtypes effectively stratified maternal and perinatal risks. GDM-Mixed subtype increased the risk of cesarean delivery, LGA, and type 2 diabetes postpartum. GDM subtypes may help personalize clinical interventions and optimize maternal and perinatal outcomes.

Protein-truncating variants in BSN are associated with severe adult-onset obesity, type 2 diabetes and fatty liver disease.

Obesity is a major risk factor for many common diseases and has a substantial heritable component. To identify new genetic determinants, we performed exome-sequence analyses for adult body mass index (BMI) in up to 587,027 individuals. We identified rare loss-of-function variants in two genes (BSN and APBA1) with effects substantially larger than those of well-established obesity genes such as MC4R. In contrast to most other obesity-related genes, rare variants in BSN and APBA1 were not associated with normal variation in childhood adiposity. Furthermore, BSN protein-truncating variants (PTVs) magnified the influence of common genetic variants associated with BMI, with a common variant polygenic score exhibiting an effect twice as large in BSN PTV carriers than in noncarriers. Finally, we explored the plasma proteomic signatures of BSN PTV carriers as well as the functional consequences of BSN deletion in human induced pluripotent stem cell-derived hypothalamic neurons. Collectively, our findings implicate degenerative processes in synaptic function in the etiology of adult-onset obesity.

Risk of a vector-borne endemic zoonosis for wildlife: Hosts, large-scale geography, and diversity of vector-host interactions for Trypanosoma cruzi.

Drivers for wildlife infection are multiple and complex, particularly for vector-borne diseases. Here, we studied the role of host competence, geographic area provenance, and diversity of vector-host interactions as drivers of wild mammal infection risk to Trypanosoma cruzi, the aetiological agent of Chagas disease. We performed a systematic sampling of wild mammals in 11 states of Mexico, from 2017 to 2018. We tested the positivity of T. cruzi with the Tc24 marker in tissues samples for 61 wild mammal species (524 specimens sampled). 26 mammal species were positive for T. cruzi, of which 11 are new hosts recorded in Mexico 75 specimens were positive and 449 were negative for T. cruzi infection, yielding an overall prevalence of 14.3%. The standardized infection risk of T. cruzi of our examined specimens was similar, no matter the host species or their geographic origins. Additionally, we used published data of mammal positives for T. cruzi to complement records of T. cruzi infection in wild mammals and inferred a trophic network of Triatoma spp. (vectors) and wild mammal species in Mexico, using spatial data-mining modelling. Infection with T. cruzi was not homogeneously distributed in the inferred trophic network. This information allowed us to develop a predictive model for T. cruzi infection risk for wild mammals in Mexico, considering risk as a function of the diversity of vector-host spatial associations in a large-scale geographic context, finding that the addition of competent vectors to a multi-host parasite system amplifies host infection risk. The diversity of vector-host interactions per se constitutes a relevant driver of infection risk because hosts and vectors are not isolated from each other.

Genotyping, sequencing and analysis of 140,000 adults from Mexico City.

The Mexico City Prospective Study is a prospective cohort of more than 150,000 adults recruited two decades ago from the urban districts of Coyoacán and Iztapalapa in Mexico City1. Here we generated genotype and exome-sequencing data for all individuals and whole-genome sequencing data for 9,950 selected individuals. We describe high levels of relatedness and substantial heterogeneity in ancestry composition across individuals. Most sequenced individuals had admixed Indigenous American, European and African ancestry, with extensive admixture from Indigenous populations in central, southern and southeastern Mexico. Indigenous Mexican segments of the genome had lower levels of coding variation but an excess of homozygous loss-of-function variants compared with segments of African and European origin. We estimated ancestry-specific allele frequencies at 142 million genomic variants, with an effective sample size of 91,856 for Indigenous Mexican ancestry at exome variants, all available through a public browser. Using whole-genome sequencing, we developed an imputation reference panel that outperforms existing panels at common variants in individuals with high proportions of central, southern and southeastern Indigenous Mexican ancestry. Our work illustrates the value of genetic studies in diverse populations and provides foundational imputation and allele frequency resources for future genetic studies in Mexico and in the United States, where the Hispanic/Latino population is predominantly of Mexican descent.

Educational and social inequalities and cause-specific mortality in Mexico City: a prospective study.

BACKGROUND: Social inequalities in adult mortality have been reported across diverse populations, but there is no large-scale prospective evidence from Mexico. We aimed to quantify social, including educational, inequalities in mortality among adults in Mexico City. METHODS: The Mexico City Prospective Study recruited 150 000 adults aged 35 years and older from two districts of Mexico City between 1998 and 2004. Participants were followed up until Jan 1, 2021 for cause-specific mortality. Cox regression analysis yielded rate ratios (RRs) for death at ages 35-74 years associated with education and examined, in exploratory analyses, the mediating effects of lifestyle and related risk factors. FINDINGS: Among 143 478 participants aged 35-74 years, there was a strong inverse association of education with premature death. Compared with participants with tertiary education, after adjustment for age and sex, those with no education had about twice the mortality rate (RR 1·84; 95% CI 1·71-1·98), equivalent to approximately 6 years lower life expectancy, with an RR of 1·78 (1·67-1·90) among participants with incomplete primary, 1·62 (1·53-1·72) with complete primary, and 1·34 (1·25-1·42) with secondary education. Education was most strongly associated with death from renal disease and acute diabetic crises (RR 3·65; 95% CI 3·05-4·38 for no education vs tertiary education) and from infectious diseases (2·67; 2·00-3·56), but there was an apparent higher rate of death from all specific causes studied with lower education, with the exception of cancer for which there was little association. Lifestyle factors (ie, smoking, alcohol drinking, and leisure time physical activity) and related physiological correlates (ie, adiposity, diabetes, and blood pressure) accounted for about four-fifths of the association of education with premature mortality. INTERPRETATION: In this Mexican population there were marked educational inequalities in premature adult mortality, which appeared to largely be accounted for by lifestyle and related risk factors. Effective interventions to reduce these risk factors could reduce inequalities and have a major impact on premature mortality. FUNDING: Wellcome Trust, the Mexican Health Ministry, the National Council of Science and Technology for Mexico, Cancer Research UK, British Heart Foundation, and the UK Medical Research Council Population Health Research Unit.

Rare coding variants in CHRNB2 reduce the likelihood of smoking.

Human genetic studies of smoking behavior have been thus far largely limited to common variants. Studying rare coding variants has the potential to identify drug targets. We performed an exome-wide association study of smoking phenotypes in up to 749,459 individuals and discovered a protective association in CHRNB2, encoding the ß2 subunit of the α4ß2 nicotine acetylcholine receptor. Rare predicted loss-of-function and likely deleterious missense variants in CHRNB2 in aggregate were associated with a 35% decreased odds for smoking heavily (odds ratio (OR) = 0.65, confidence interval (CI) = 0.56-0.76, P = 1.9 × 10-8). An independent common variant association in the protective direction ( rs2072659 ; OR = 0.96; CI = 0.94-0.98; P = 5.3 × 10-6) was also evident, suggesting an allelic series. Our findings in humans align with decades-old experimental observations in mice that ß2 loss abolishes nicotine-mediated neuronal responses and attenuates nicotine self-administration. Our genetic discovery will inspire future drug designs targeting CHRNB2 in the brain for the treatment of nicotine addiction.

Sex differences in the influence of type 2 diabetes (T2D)-related genes, parental history of T2D, and obesity on T2D development: a case-control study.

BACKGROUND: This study investigated the effect of sex and age at type 2 diabetes (T2D) diagnosis on the influence of T2D-related genes, parental history of T2D, and obesity on T2D development. METHODS: In this case-control study, 1012 T2D cases and 1008 healthy subjects were selected from the Diabetes in Mexico Study database. Participants were stratified by sex and age at T2D diagnosis (early, ≤ 45 years; late, ≥ 46 years). Sixty-nine T2D-associated single nucleotide polymorphisms were explored and the percentage contribution (R2) of T2D-related genes, parental history of T2D, and obesity (body mass index [BMI] and waist-hip ratio [WHR]) on T2D development was calculated using univariate and multivariate logistic regression models. RESULTS: T2D-related genes influenced T2D development most in males who were diagnosed early (R2 = 23.5%; females, R2 = 13.5%; males and females diagnosed late, R2 = 11.9% and R2 = 7.3%, respectively). With an early diagnosis, insulin production-related genes were more influential in males (76.0% of R2) while peripheral insulin resistance-associated genes were more influential in females (52.3% of R2). With a late diagnosis, insulin production-related genes from chromosome region 11p15.5 notably influenced males while peripheral insulin resistance and genes associated with inflammation and other processes notably influenced females. Influence of parental history was higher among those diagnosed early (males, 19.9%; females, 17.5%) versus late (males, 6.4%; females, 5,3%). Unilateral maternal T2D history was more influential than paternal T2D history. BMI influenced T2D development for all, while WHR exclusively influenced males. CONCLUSIONS: The influence of T2D-related genes, maternal T2D history, and fat distribution on T2D development was greater in males than females.

The prevalence of diabetes worldwide is slightly higher in men than in women, particularly in those aged 50 or younger (16.5% for men versus 13.5% for women). This suggests that hormonal differences could be critical in early development of Type 2 diabetes. Some known factors previously associated with T2D, such as genes, parental history of diabetes and obesity, could have a differential influence between both sexes for the development of T2D. We compared these factors between 1008 healthy individual and 1012 TD2 patients. In this comparison, we calculated the percentage of variability of the disease explained by each factor. As expected, the most noticeable differences between men and women were observed in T2D diagnoses before age 46. Genes had a greater effect in men than in women (23.5% vs. 13.5%). While genes involved in insulin production have a greater influence on men, genes involved in peripheric insulin resistance have a greater influence on women. The overall parental history of T2D influences similarly in males (19.9%) and females (17.5%), however, the unilateral genetic influence of the mother was much greater in males than in females. The influence of global and abdominal obesity played a greater role in men than in women. In T2D diagnoses after age of 45, the influence of genes and parental history of diabetes decreases markedly, and the relative influence of global obesity augments. However, while genes linked to insulin resistance and inflammation predominate in females, genes linked to insulin secretion predominate in males.

A deep catalog of protein-coding variation in 985,830 individuals.

Coding variants that have significant impact on function can provide insights into the biology of a gene but are typically rare in the population. Identifying and ascertaining the frequency of such rare variants requires very large sample sizes. Here, we present the largest catalog of human protein-coding variation to date, derived from exome sequencing of 985,830 individuals of diverse ancestry to serve as a rich resource for studying rare coding variants. Individuals of African, Admixed American, East Asian, Middle Eastern, and South Asian ancestry account for 20% of this Exome dataset. Our catalog of variants includes approximately 10.5 million missense (54% novel) and 1.1 million predicted loss-of-function (pLOF) variants (65% novel, 53% observed only once). We identified individuals with rare homozygous pLOF variants in 4,874 genes, and for 1,838 of these this work is the first to document at least one pLOF homozygote. Additional insights from the RGC-ME dataset include 1) improved estimates of selection against heterozygous loss-of-function and identification of 3,459 genes intolerant to loss-of-function, 83 of which were previously assessed as tolerant to loss-of-function and 1,241 that lack disease annotations; 2) identification of regions depleted of missense variation in 457 genes that are tolerant to loss-of-function; 3) functional interpretation for 10,708 variants of unknown or conflicting significance reported in ClinVar as cryptic splice sites using splicing score thresholds based on empirical variant deleteriousness scores derived from RGC-ME; and 4) an observation that approximately 3% of sequenced individuals carry a clinically actionable genetic variant in the ACMG SF 3.1 list of genes. We make this important resource of coding variation available to the public through a variant allele frequency browser. We anticipate that this report and the RGC-ME dataset will serve as a valuable reference for understanding rare coding variation and help advance precision medicine efforts.

MIDO GDM: an innovative artificial intelligence-based prediction model for the development of gestational diabetes in Mexican women.

Given the barriers to early detection of gestational diabetes mellitus (GDM), this study aimed to develop an artificial intelligence (AI)-based prediction model for GDM in pregnant Mexican women. Data were retrieved from 1709 pregnant women who participated in the multicenter prospective cohort study 'Cuido mi embarazo'. A machine-learning-driven method was used to select the best predictive variables for GDM risk: age, family history of type 2 diabetes, previous diagnosis of hypertension, pregestational body mass index, gestational week, parity, birth weight of last child, and random capillary glucose. An artificial neural network approach was then used to build the model, which achieved a high level of accuracy (70.3%) and sensitivity (83.3%) for identifying women at high risk of developing GDM. This AI-based model will be applied throughout Mexico to improve the timing and quality of GDM interventions. Given the ease of obtaining the model variables, this model is expected to be clinically strategic, allowing prioritization of preventative treatment and promising a paradigm shift in prevention and primary healthcare during pregnancy. This AI model uses variables that are easily collected to identify pregnant women at risk of developing GDM with a high level of accuracy and precision.

Evaluation of effective coverage for type 2 diabetes in Mexican primary care health information systems: a retrospective registry analysis.

BACKGROUND: As the leading cause of disability and the fourth leading cause of premature death in Mexico, type 2 diabetes (T2D) represents a serious public health concern. The incidence of diabetes has increased dramatically in recent years, and data from the Mexican National Health and Nutrition Survey (ENSANUT) indicate that many people remain undiagnosed. Persistent socioeconomic health care barriers exacerbate this situation, as T2D morbidity and mortality are worsened in vulnerable populations, such as those without social security. We evaluated the performance of public primary health centers (PHCs) in T2D medical attention through the measure of effective coverage (EC, a combined measure of health care need, use, and quality) at national, state, health jurisdiction, and municipality levels. METHODS: This retrospective analysis used blinded data recorded during 2017 in the Non-communicable Diseases National Information System (SIC) and T2D prevalence reported in 2018 ENSANUT to evaluate the EC achieved. We included individuals ≥ 20 years old without social security who did not declare the use of private health care services. Each EC component (need, use, and quality) was estimated based on the Shengelia adapted framework. The Kruskal-Wallis test was applied to evaluate the associations among EC quintiles and demographics. RESULTS: In 2017, 26.5 million individuals, aged ≥ 20 years, without social security, and without the use of private health care services, were under the care of 12,086 PHCs. The national prevalence of T2D was 10.3%, equivalent to 2.6 million people living with T2D in need of primary health care. Large contrasts were seen among EC components between and within Mexican states. We found that only 37.1% of the above individuals received health services at PHCs and of them, 25.8% improved their metabolic condition. The national EC was 9.3%, and the range (by health jurisdiction) was 0.2%-38.6%, representing a large geographic disparity in EC. We found an evident disconnect among need, utilization, and quality rates across the country. CONCLUSIONS: Expansion and improvement of EC are urgently needed to address the growing number of people living with T2D in Mexico, particularly in states with vulnerable populations.

Development and validation of a multivariable genotype-informed gestational diabetes prediction algorithm for clinical use in the Mexican population: insights into susceptibility mechanisms.

INTRODUCTION: Gestational diabetes mellitus (GDM) is underdiagnosed in Mexico. Early GDM risk stratification through prediction modeling is expected to improve preventative care. We developed a GDM risk assessment model that integrates both genetic and clinical variables. RESEARCH DESIGN AND METHODS: Data from pregnant Mexican women enrolled in the 'Cuido mi Embarazo' (CME) cohort were used for development (107 cases, 469 controls) and data from the 'Mónica Pretelini Sáenz' Maternal Perinatal Hospital (HMPMPS) cohort were used for external validation (32 cases, 199 controls). A 2-hour oral glucose tolerance test (OGTT) with 75 g glucose performed at 24-28 gestational weeks was used to diagnose GDM. A total of 114 single-nucleotide polymorphisms (SNPs) with reported predictive power were selected for evaluation. Blood samples collected during the OGTT were used for SNP analysis. The CME cohort was randomly divided into training (70% of the cohort) and testing datasets (30% of the cohort). The training dataset was divided into 10 groups, 9 to build the predictive model and 1 for validation. The model was further validated using the testing dataset and the HMPMPS cohort. RESULTS: Nineteen attributes (14 SNPs and 5 clinical variables) were significantly associated with the outcome; 11 SNPs and 4 clinical variables were included in the GDM prediction regression model and applied to the training dataset. The algorithm was highly predictive, with an area under the curve (AUC) of 0.7507, 79% sensitivity, and 71% specificity and adequately powered to discriminate between cases and controls. On further validation, the training dataset and HMPMPS cohort had AUCs of 0.8256 and 0.8001, respectively. CONCLUSIONS: We developed a predictive model using both genetic and clinical factors to identify Mexican women at risk of developing GDM. These findings may contribute to a greater understanding of metabolic functions that underlie elevated GDM risk and support personalized patient recommendations.

The Low Variability of Tc24 in Trypanosoma cruzi TcI as an Advantage for Chagas Disease Prophylaxis and Diagnosis in Mexico.

(1) Background: Chagas disease is the main neglected tropical disease in America. It is estimated that around 6 million people are currently infected with the parasite in Latin America, and 25 million live in endemic areas with active transmission. The disease causes an estimated economic loss of USD 24 billion dollars annually, with a loss of 75,200 working years per year of life; it is responsible for around ~12,000 deaths annually. Although Mexico is an endemic country that recorded 10,186 new cases of Chagas disease during the period of 1990-2017, few studies have evaluated the genetic diversity of genes that could be involved in the prophylaxis and/or diagnosis of the parasite. One of the possible candidates proposed as a vaccine target is the 24 kDa trypomastigote excretory-secretory protein, Tc24, whose protection is linked to the stimulation of T. cruzi-specific CD8+ immune responses. (2) Methods: The aim of the present study was to evaluate the fine-scale genetic diversity and structure of Tc24 in T. cruzi isolates from Mexico, and to compare them with other populations reported in the Americas with the aim to reconsider the potential role of Tc24 as a key candidate for the prophylaxis and improvement of the diagnosis of Chagas disease in Mexico. (3) Results: Of the 25 Mexican isolates analysed, 48% (12) were recovered from humans and 24% (6) recovered from Triatoma barberi and Triatoma dimidiata. Phylogenetic inferences revealed a polytomy in the T. cruzi clade with two defined subgroups, one formed by all sequences of the DTU I and the other formed by DTU II-VI; both subgroups had high branch support. Genetic population analysis detected a single (monomorphic) haplotype of TcI throughout the entire distribution across both Mexico and South America. This information was supported by Nei's pairwise distances, where the sequences of TcI showed no genetic differences. (4) Conclusions: Given that both previous studies and the findings of the present work confirmed that TcI is the only genotype detected from human isolates obtained from various states of Mexico, and that there is no significant genetic variability in any of them, it is possible to propose the development of in silico strategies for the production of antigens that optimise the diagnosis of Chagas disease, such as quantitative ELISA methods that use this region of Tc24.

Diabetes and infectious disease mortality in Mexico City.

INTRODUCTION: Although higher risks of infectious diseases among individuals with diabetes have long been recognized, the magnitude of these risks is poorly described, particularly in lower income settings. This study sought to assess the risk of death from infection associated with diabetes in Mexico. RESEARCH DESIGN AND METHODS: Between 1998 and 2004, a total of 159 755 adults ≥35 years were recruited from Mexico City and followed up until January 2021 for cause-specific mortality. Cox regression yielded adjusted rate ratios (RR) for death due to infection associated with previously diagnosed and undiagnosed (HbA1c ≥6.5%) diabetes and, among participants with previously diagnosed diabetes, with duration of diabetes and with HbA1c. RESULTS: Among 130 997 participants aged 35-74 and without other prior chronic diseases at recruitment, 12.3% had previously diagnosed diabetes, with a mean (SD) HbA1c of 9.1% (2.5%), and 4.9% had undiagnosed diabetes. During 2.1 million person-years of follow-up, 2030 deaths due to infectious causes were recorded at ages 35-74. Previously diagnosed diabetes was associated with an RR for death from infection of 4.48 (95% CI 4.05-4.95), compared with participants without diabetes, with notably strong associations with death from urinary tract (9.68 (7.07-13.3)) and skin, bone and connective tissue (9.19 (5.92-14.3)) infections and septicemia (8.37 (5.97-11.7)). In those with previously diagnosed diabetes, longer diabetes duration (1.03 (1.02-1.05) per 1 year) and higher HbA1c (1.12 (1.08-1.15) per 1.0%) were independently associated with higher risk of death due to infection. Even among participants with undiagnosed diabetes, the risk of death due to infection was nearly treble the risk of those without diabetes (2.69 (2.31-3.13)). CONCLUSIONS: In this study of Mexican adults, diabetes was common, frequently poorly controlled, and associated with much higher risks of death due to infection than observed previously, accounting for approximately one-third of all premature mortality due to infection.

Body Composition and Risk of Vascular-Metabolic Mortality Risk in 113 000 Mexican Men and Women Without Prior Chronic Disease.

Background Body-mass index is the sum of fat mass index (FMI) and lean mass index (LMI), which vary by age, sex, and impact on disease outcomes. We investigated the separate and joint relevance of FMI and LMI with vascular-metabolic causes of death in Mexican adults. Methods and Results A total of 113 025 adults aged 35 to 74 years and free from diabetes or other chronic diseases when recruited into the Mexico City Prospective Study were followed for 19 years. Cox models estimated sex-specific death rate ratios from vascular-metabolic causes after adjustment for confounders and exclusion of the first 5 years of follow-up. To account for the strong correlation between FMI and LMI, additional models estimated rate ratios associated with "residual FMI" and "residual LMI" (ie, the residuals from linear regression analyses of FMI on LMI, or vice versa). In both sexes, higher FMI and LMI were associated with higher risks of vascular-metabolic mortality. For a given (ie, fixed) level of LMI, the rate ratio (95% CI) for vascular-metabolic mortality per 1 kg/m2 higher residual FMI strengthened and was higher in women (1.52 [1.38-1.68]) than in men (1.19 [1.13-1.25]). By contrast, for a given level of FMI, higher residual LMI was inversely associated with vascular-metabolic mortality (rate ratio per 1 kg/m2 0.67 [0.56-0.80] in women and 0.94 [0.90-0.98] in men). Conclusions In this study, higher residual FMI was more strongly associated with vascular-metabolic mortality in women than in men. Conversely, higher residual LMI was inversely associated with vascular-metabolic mortality, particularly in women.

Novel clinical and immunological features associated with persistent post-acute sequelae of COVID-19 after six months of follow-up: a pilot study.

BACKGROUND: Currently, there is scant information regarding the features associated to the persistence of post-COVID-19 syndrome, which is the main aim of the present study. METHODS: A cohort study of 102 COVID-19 patients was conducted. The post-COVID-19 symptoms were assessed by a standardised questionnaire. Lymphocyte immunophenotyping was performed by flow cytometry and chemokines/cytokines, neutrophil extracellular traps, the tripartite motif 63, anti-cellular, and anti-SARS-CoV-2 IgG antibodies were addressed in serum. The primary outcome was the persistence of post-COVID-19 syndrome after six months follow-up. RESULTS: Thirteen patients (12.7%) developed the primary outcome and had a more frequent history of post-COVID-19 syndrome 3 months after infection onset (p = .044), increased levels of IL-1α (p = .011) and IP-10 (p = .037) and increased CD57 expression in CD8+ T cells (p = .003). There was a trend towards higher levels of IFN-γ (p = .051), IL-1ß (p = .062) and IL-6 (p = .087). The history of post COVID-19 in the previous 3 months, obesity, baseline serum MIP-1α and IP-10, and CD57 expression in CD8+ T cells were independently associated with the persistence of post-COVID-19 syndrome. CONCLUSION: Our data suggest an important relationship between a pro-inflammatory state mediated through metabolic pathways related to obesity and increased cellular senescence as a key element in the persistence of post-COVID-19 syndrome at six months of follow-up.

Type 2 diabetes epidemic in Mexico. Burden of disease 1990-2021 analysis and implications for public policies.

BACKGROUND: Mexico faces a challenge due to the burden imposed by type 2 diabetes (T2D). OBJECTIVE: To analyze T2D epidemiology and burden in Mexico from 1990 to 2021, at the national and state levels. MATERIAL AND METHODS: Estimates from the Global Burden of Disease 2021 study were used to evaluate the prevalence, incidence, mortality, fatal and non-fatal burden. Metabolic, environmental and behavioral factors were considered. Comparative analyses were carried out by gender, age and state of the country. RESULTS: The prevalence of T2D increased by 25%. The incidence increased in those younger than 45 years, with a mortality decrease being found among women. The rate of disability-adjusted life years (DALY) showed an increase in all states, from 45.2% in Nuevo León to 237.6% in Tabasco. In 2021, T2D caused the loss of 3.1 million DALYs, which accounted for 6.6% of total burden in Mexico, out of which 64% was due to premature deaths. Diabetic neuropathy affected 47%, and there were 270,000 cases of visual impairment; 66.3% of the burden was attributed to obesity. CONCLUSIONS: Comprehensive policies are urgently needed in order to reduce the burden of T2D in Mexico, through standardized guidelines, evidence-based strategies and technological resources that improve medical care accessibility and efficiency.

ANTECEDENTES: México enfrenta un desafío por la carga que representa la diabetes tipo 2 (DT2). OBJETIVO: Analizar la epidemiología y la carga de DT2 en México de 1990 a 2021 en los ámbitos nacional y estatal. MATERIAL Y MÉTODOS: Se empleó el Global Burden of Disease 2021 para evaluar prevalencia, incidencia, mortalidad, carga letal y no letal. Se consideraron factores metabólicos, ambientales y de comportamiento. Se realizó análisis comparativo por sexo, edad y entidad federativa. RESULTADOS: Se incrementó la prevalencia de DT2 en 25 % y la incidencia en menores de 45 años; la mortalidad en mujeres disminuyó. La tasa de años de vida saludable (AVISA) perdidos se incrementó en todos los estados, entre 45.2 % en Nuevo León y 237.6 % en Tabasco. En 2021, la DT2 ocasionó 3.1 millones de AVISA perdidos, que representaron 6.6 % de la carga total en México, de la cual 64 % se atribuyó a muertes prematuras. La neuropatía diabética afectó a 47 % y las afecciones visuales a 270 000 personas; 66.3 % de la carga se atribuyó a obesidad. CONCLUSIONES: Urgen políticas integrales para reducir la carga de DT2 en México, mediante pautas estandarizadas, estrategias basadas en evidencia y recursos tecnológicos que mejoren la accesibilidad y eficiencia de la atención médica.

Diagnostic Accuracy of Capillary Blood Glucometer Testing for Gestational Diabetes.

Purpose: Few pregnant women in low-resource settings are screened for gestational diabetes mellitus (GDM) using the gold standard oral glucose tolerance test (OGTT). This study compared capillary blood glucose testing with 2-h plasma glucose measurements obtained using the 75-g OGTT to screen for GDM at primary healthcare clinics in Mexico. Patients and Methods: Pregnant women who participated in a previous prospective multicenter longitudinal cohort study and who had not been previously diagnosed with diabetes were included. Participants were evaluated using the plasmatic 2-h 75-g OGTT with simultaneous capillary blood glucose measurements using a glucometer. The study endpoint was the comparability of the glucometer results to the gold standard OGTT when collected simultaneously. Sensitivity, specificity, and area under the curve of the glucose measurements obtained for capillary blood compared with venous plasma (gold standard) were calculated to determine diagnostic accuracy. Results: The study included 947 pregnant women who had simultaneous glucose measurements available (blood capillary [glucometer] and venous blood OGTT). Overall, capillary blood glucose testing was very sensitive (89.47%); the specificity was 66.58% and the area under the curve (95% confidence interval) was 0.78 (0.74-0.81). The sensitivity, specificity and area under the curve of each capillary measurement were: 89.47%, 66.58% and 0.78 (0.74-0.82) for the fasting measurement, 91.53%, 93.24% and 0.92 (0.88-0.96) for the one-hour measurement, and 89.80%, 93.32%, 0.91 (0.87-0.95) for the second-hour measurement, respectively. No adverse events were reported. Conclusion: Capillary OGTT is a valid alternative to the gold standard OGTT for screening of GDM in low-resource situations or in situations where there are other limitations to performing the OGTT as part of primary healthcare services.

MIDO COVID: A digital public health strategy designed to tackle chronic disease and the COVID-19 pandemic in Mexico.

Screening, prevention, and management of non-communicable diseases (NCDs, including obesity, hypertension, and type 2 diabetes) is the core function of Integrated Measurement for Early Detection (MIDO), a digital strategy developed by the Carlos Slim Foundation in Mexico. An extension of this strategy, MIDO COVID, was developed to address the need for an integrated plan in primary health care during the COVID-19 pandemic. MIDO COVID facilitates planning, surveillance, testing, and clinical management of SARS-CoV-2 infections and the major NCDs and their pre-disease states, to streamline the continuum of care. MIDO COVID screening was applied in 1063 Carso Group workplaces in 190 municipalities of the 32 Mexican states. Staff were trained to screen healthy workers for NCDs using a questionnaire, anthropomorphic measurements, and blood work; healthy individuals returning to work also received a SARS-CoV-2 antibody test. Between June 26 and December 31, 2020, 58,277 asymptomatic individuals underwent screening. The prevalence of obesity, hypertension, and type 2 diabetes was 32.1%, 25.7%, and 9.7% respectively. Only 2.2%, 8.8%, and 4.5% of individuals, respectively, were previously aware of their condition. Pre-obesity was identified in 38.6%, pre-hypertension in 17.4%, and prediabetes in 7.5% of the population. Risk of SARS-CoV-2 infection was highest for individuals with multiple NCDs. Many Mexicans are unaware of their health status and potentially increased risk of COVID-19 and serious complications. As a universal strategy implemented regardless of social factors, MIDO COVID promotes equity in access to health care prevention and early stage detection of NCDs; the information gained may help inform decisionmakers regarding prioritising vulnerable populations for immunisation.