Dataset Information

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

ABSTRACT: 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.

SUBMITTER: Ziyatdinov A

PROVIDER: S-EPMC10600010 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature

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

Ziyatdinov Andrey A Torres Jason J Alegre-Díaz Jesús J Backman Joshua J Mbatchou Joelle J Turner Michael M Gaynor Sheila M SM Joseph Tyler T Zou Yuxin Y Liu Daren D Wade Rachel R Staples Jeffrey J Panea Razvan R Popov Alex A Bai Xiaodong X Balasubramanian Suganthi S Habegger Lukas L Lanche Rouel R Lopez Alex A Maxwell Evan E Jones Marcus M García-Ortiz Humberto H Ramirez-Reyes Raul R Santacruz-Benítez Rogelio R Nag Abhishek A Smith Katherine R KR Damask Amy A Lin Nan N Paulding Charles C Reppell Mark M Zöllner Sebastian S Jorgenson Eric E Salerno William W Petrovski Slavé S Overton John J Reid Jeffrey J Thornton Timothy A TA Abecasis Gonçalo G Berumen Jaime J Orozco-Orozco Lorena L Collins Rory R Baras Aris A Hill Michael R MR Emberson Jonathan R JR Marchini Jonathan J Kuri-Morales Pablo P Tapia-Conyer Roberto R

Nature 20231011 7984

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 City<sup>1</sup>. 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 America ...[more]

PMID: 37821707

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Project description:Vaccines are effective to reduce COVID-19 related outcomes, but universal vaccination campaigns can reveal within-country access inequities. Mexico City has had high rates of COVID-19 related morbidity and mortality and a population survey warned that vaccine acceptance was lowest in older adults. Since February 2021, Mexico started a universal and free vaccination campaign prioritizing older adults. By April 17, every older adult in Mexico City had been eligible to receive the first dose. A week later, we conducted a telephone survey representative of older adults residing in Mexico City (n = 503). We asked if they received their first dose and, if they haven't, we followed-up with an open question to register their reasons. In addition to sociodemographic characteristics and food insecurity, we also inquired about vaccine hesitancy, health concerns related to COVID-19, self-rated health, comorbidities, frailty, and depression. The objective of the study was to identify the main barriers to receive the first dose of the vaccine. We estimated descriptive statistics and logistic regression models. Results show that 7.6% of older adults in Mexico City did not receive their first dose. Barriers for not receiving it were vaccine hesitancy (60.4%), not having COVID-19 health concerns (46.4%), poor self-rated health (46.7%), a previous diagnosis of depression (35.7%), low socioeconomic status (65.4%), and household food insecurity (59.8%). Responses to the open question clustered in four themes: misinformation about the process (30%), distrust of the vaccine (24%), personal health problems (24%), and difficulties to get an appointment (22%). Logistic regression models adjusted for vaccine hesitancy and revealed two distinct reasons for not having their first dose: 1) vaccine hesitancy and misinformation on COVID-19, and 2) household food insecurity. Reaching these two groups requires active and differentiated public-health measures; the first with additional information from trusted sources, and the second by facilitating vaccination in neighborhoods with high levels of food insecurity and informal labor, where missing a day's work is a strong disincentive. Vaccination campaigns need an equity lens to reach universal coverage; ensuring full access demands thorough and carefully tailored new interventions.

Project description:UNLABELLED:Geostatistical interpolation methods to estimate individual exposure to outdoor air pollutants can be used in pregnancy cohorts where personal exposure data are not collected. Our objectives were to a) develop four assessment methods (citywide average (CWA); nearest monitor (NM); inverse distance weighting (IDW); and ordinary Kriging (OK)), and b) compare daily metrics and cross-validations of interpolation models. We obtained 2008 hourly data from Mexico City's outdoor air monitoring network for PM10, PM2.5, O3, CO, NO2, and SO2 and constructed daily exposure metrics for 1,000 simulated individual locations across five populated geographic zones. Descriptive statistics from all methods were calculated for dry and wet seasons, and by zone. We also evaluated IDW and OK methods' ability to predict measured concentrations at monitors using cross validation and a coefficient of variation (COV). All methods were performed using SAS 9.3, except ordinary Kriging which was modeled using R's gstat package. Overall, mean concentrations and standard deviations were similar among the different methods for each pollutant. Correlations between methods were generally high (r=0.77 to 0.99). However, ranges of estimated concentrations determined by NM, IDW, and OK were wider than the ranges for CWA. Root mean square errors for OK were consistently equal to or lower than for the IDW method. OK standard errors varied considerably between pollutants and the computed COVs ranged from 0.46 (least error) for SO2 and PM10 to 3.91 (most error) for PM2.5. OK predicted concentrations measured at the monitors better than IDW and NM. Given the similarity in results for the exposure methods, OK is preferred because this method alone provides predicted standard errors which can be incorporated in statistical models. The daily estimated exposures calculated using these different exposure methods provide flexibility to evaluate multiple windows of exposure during pregnancy, not just trimester or pregnancy-long exposures. IMPLICATIONS:Many studies evaluating associations between outdoor air pollution and adverse pregnancy outcomes rely on outdoor air pollution monitoring data linked to information gathered from large birth registries, and often lack residence location information needed to estimate individual exposure. This study simulated 1,000 residential locations to evaluate four air pollution exposure assessment methods, and describes possible exposure misclassification from using spatial averaging versus geostatistical interpolation models. An implication of this work is that policies to reduce air pollution and exposure among pregnant women based on epidemiologic literature should take into account possible error in estimates of effect when spatial averages alone are evaluated.

Dataset Information

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

Publications

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

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