Diego Aguilar-Ramirez

Human populations differ in disease prevalence and phenotypes, but the extent to which differences are caused by genetic factors is unknown for most complex traits. Comparing phenotypic means across populations is confounded by environmental differences and using polygenic predictors can lead to biased inference ^1,2 . Family-based analyses of people of genetically admixed ancestry enable estimation of ancestry effects unconfounded by ancestry–environment correlations. Here we leverage genetic data from admixed adults in the Mexico City Prospective Study ^3,4 to estimate within-family ancestry effects ⁵ . We assessed genetic ancestry and 15 complex traits in 52,583 unrelated people and 39,714 relatives from 17,627 families. At the population level, relative to European ancestry, the effect of Indigenous American ancestry was −1.98 s.d. ( P < 2 × 10 ⁻¹⁶ ) for height and a natural log odds ratio of 1.73 (95% confidence interval, 1.54–1.92) for type 2 diabetes. Within families, the effect of Indigenous American ancestry was −1.51 s.d. ( P = 10 ⁻⁸ ) for height and natural log odds ratio of 5.13 (95% confidence interval, 2.48–7.78) for type 2 diabetes. These effects are supported by between-ancestry differences in trait-increasing allele counts and evidence of selection at trait-associated loci. We found no within-family ancestry effect on educational attainment or other traits despite significant associations at the population level, implying environmental causes or confounding. Overall, this study provides an experimental design to study between-ancestry genetic effects and identifies significant ancestry differences for height, type 2 diabetes and metabolic traits in a genetically diverse population from Mexico City.

Despite metabolomics transforming our understanding of risk factors and aetiology of metabolic diseases, profiling is rarely performed for people of non-European ancestries, on whom much of metabolic disease burden falls. Metabolome-wide association studies (MWAS) can be performed using genetic scores to predict metabolomic traits, helping address these inequities; however, their performance in populations of admixed American (AMR) ancestries is unexplored. We evaluated 141 genetic scores, developed in an INTERVAL Study sample of European (EUR) genetic ancestries, in the Mexico City Prospective Study (MCPS; n =132,336), obtaining a median predictive R ² of 0.027. Training Bayesian ridge models within MCPS substantially improved performance, with a median R ² of 0.083 on a withheld 20% subset. MCPS-trained models also outperformed INTERVAL-trained models among UK Biobank participants of AMR ancestries ( n =600; median R ² : 0.070 vs. 0.046). Finally, among AMR participants of the All of Us cohort, using MCPS-trained (vs. INTERVAL-trained) models to predict metabolomic traits yielded five times as many significant associations (FDR-corrected P <0.05) across three cardiometabolic diseases: ischaemic heart disease, type 2 diabetes, and chronic kidney disease. The genetic scores are openly available at the OmicsPred portal ( www.OmicsPred.org ), enabling better-powered analyses in diverse AMR cohorts and helping reduce global inequities in omics research.

Reproduction is one of the most fundamental biological processes in the human body, yet the molecules governing it remain incompletely understood. Here, we have characterized the role of PKHD1L1 and its globally relatively common splice donor variant rs17368310 in female fertility. We demonstrate estrogen-responsive expression of PKHD1L1 in the human endometrial and Fallopian tube epithelium, identify the change in the rs17368310 mRNA sequence in endometrial tissue, and assess the possible effects of the variant on the PKHD1L1 protein through structural modeling. We reveal that women homozygous for rs17368310 have a persistently lower child count compared to other genotypes not only among all women but also among women who have undergone medical treatments for infertility in the Finnish population. We further show that rs17368310 associates with female infertility-related traits also in the Mexican population. These findings elucidate the effects of rs17368310 on fertility in millions of reproductive-age women across different populations.

Background: The causal relevance of different adiposity markers to infection-related death remains uncertain. We estimated the lifelong associations of genetically predicted adiposity traits with infection-related mortality among 126 491 Mexican adults. Methods: Mendelian randomization (MR) using trans-ancestry instruments for body mass index (BMI), fat-mass percentage (FM%), and waist and hip circumference was used to estimate causal effects on infection-related mortality at ages 35–74 years, overall and across six infection subtypes. Multivariable MR was used to assess independent associations. Results: Genetic instruments explained 1.6%–3.5% of the variance in adiposity markers and the strengths of their associations with the markers were similar in men and women. Over 20 years, 2592 infection-related deaths occurred at ages 35–74 years. Genetically predicted adiposity was strongly associated with infection mortality, with the strongest association for FM% [hazard ratio (HR) per 1-SD higher level: 2.54; 95% confidence interval (CI) 1.91–3.38] and the weakest for hip circumference (HR 1.61; 95% CI 1.30–2.01). Associations were consistent across six subtypes: respiratory; urinary tract; gastrointestinal; sepsis; skin, bone, and connective tissue; and other infections. For BMI and FM%, mutual adjustment for waist and hip circumference reduced the associations by nearly one-third. For waist circumference, adjustment for BMI and hip circumference reduced the association by more than half, while, for hip circumference, mutual adjustment for BMI and waist circumference almost eliminated its association. Sensitivity analyses supported the main conclusions. Conclusion: Higher adiposity is causally associated with a higher risk of infection-related mortality in Mexican adults. Strategies to reduce the population levels of adiposity in Mexico could contribute to lowering mortality from infection.

Type 2 diabetes (T2D) is a highly heritable, polygenic disease with over 600 loci identified through genome-wide association studies (GWAS). However, despite possessing unique genetic variation shaped by demographic history and admixture, Latin American populations remain markedly underrepresented in global genomic research. To address this gap, we conducted genome- and exome-wide analyses of 19,431 T2D cases and 105,611 controls from the Mexico City Prospective Study (MCPS). We identified 86 independent GWAS associations, including 21 novel signals, 15 of which replicated in external cohorts. Risk alleles at novel loci were enriched in individuals with Indigenous American ancestry. Exome analyses revealed rare and ultra-rare missense variants with substantial risk effects at HNF1A and GCK , as well as a protein-damaging variant in SLC30A8 that reduced T2D risk by 45% in carriers. Integrative analyses indicate that T2D genetic architecture in Mexico is predominantly driven by common regulatory variation acting in the endocrine pancreas. Polygenic risk scores strongly stratified T2D risk and transferred to Indigenous Mexican populations. These findings demonstrate the power of large-scale genetic discovery in diverse populations to refine disease architecture and identify loci with potential therapeutic relevance.

Aims: Most polygenic risk scores (PRSs) for coronary heart disease (CHD) are derived from European ancestry populations. This paper evaluates the performance of CHD PRSs in a Mexican population. Methods and results: 133 207 participants aged 35–79 years from the Mexico City Prospective Study were included. Eight PRSs (comprising 44–6 472 620 polymorphisms) were selected for prediction of CHD (defined as self-reported prior heart attack or angina, or CHD death before age 80 years). Logistic regression was adjusted for age, sex, and the first seven genetic principal components, before and after adjustment for other cardiovascular risk factors. The area under the receiving operating characteristic curve (‘C-statistic’) was also estimated. Of the included participants, 67% were women, the mean (±SD) age was 51 ± 12 years, and Indigenous American ancestry averaged 67%. CHD was documented for 5163 participants (3.9%), including 1901 prevalent and 3479 fatal cases. All eight PRSs were positively and log-linearly associated with CHD, with odds ratios (ORs) per 1 SD PRS increase ranging from 1.05 (95% CI, 1.03–1.08) to 1.29 (95% CI, 1.25–1.33). Associations were consistent across strata of age and ancestry and were independent of other vascular risk factors. For six PRSs, however, associations were substantially stronger in men than women. Multi-ancestry PRSs outperformed Eurocentric-ancestry PRSs. Despite remaining predictive of risk independently of established non-genetic risk factors, inclusion of a PRS into a risk model did not increase the C-statistic noticeably. Conclusion: In this Mexican population, existing PRSs predicted CHD independently of established vascular risk factors, particularly for men. PRSs better capturing genetic variation in Latin American people may further enhance risk prediction in such populations.

Background: Persistent hyperglycaemia in diabetes can cause weight loss, distorting the association of adiposity with mortality. We estimated the lifelong associations of genetically predicted body mass index (BMI) with 52 causes of death among 125 003 Mexican adults, in whom persistent hyperglycaemia in diabetes was common. Methods: A trans-ancestry genetic instrument for BMI (from 724 BMI-associated single-nucleotide polymorphisms) estimated the causal relevance of BMI to mortality before age 75 years, stratified by sex and adjusted for age and underlying ancestry structure, using a one-sample Mendelian randomization (MR) approach. Two-sample MR and other sensitivity analyses were also performed. Results: The genetic instrument explained 3% of the BMI variation and predicted BMI similarly in men and women. Each 5-kg/m2 higher genetically predicted BMI was associated with nearly a doubling in the risk of all-cause mortality at ages 35–74 years [13 066 deaths; hazard ratio (HR) 1.80, 95% confidence interval (CI) 1.63–2.00]. Hazard ratios were greater for vascular-metabolic (n = 7111; HR 2.15, 95% CI 1.87–2.48) than for non-vascular-metabolic causes (n = 5955; HR 1.47, 95% CI 1.27–1.71) and particularly strong for renal (n = 2034; HR 3.59, 95% CI 2.76–4.67), acute diabetic crises (n = 557; HR 2.70, 95% CI 1.64–4.44), and infective deaths (n = 811; HR 2.61, 95% CI 1.73–3.92). For all-cause mortality, HRs were somewhat greater at younger ages compared with older ages, and slightly larger in those with a higher proportion of Indigenous American ancestry. The strength of the association with mortality was reduced by more than half after simple adjustment for genetic predisposition to diabetes. Sensitivity analyses supported the main conclusions. Conclusion: In this Mexican population, genetically predicted lifelong BMI was strongly related to mortality and mediated substantially through diabetes.

OBJECTIVE To validate AnthropoAge, a new metric of biological age (BA), for prediction of all-cause mortality and age-related outcomes and characterize population-specific aging patterns using multinational longitudinal cohorts. METHODS We analyzed harmonized multinational data from the Gateway to Global Aging, including studies from the US, England, Mexico, Costa Rica, and China. We used body mass index and waist-to-height ratio to estimate AnthropoAge and AnthropoAgeAccel in participants aged 50-90 years old as proxies of BA and age acceleration, respectively. We compared the predictive capacity for all-cause mortality of AnthropoAge and chronological age (CA) using Cox models, described aging trends in all countries and explored the utility of longitudinal assessments of AnthropoAgeAccel to predict new-onset functional decline and age-related diseases using generalized estimating equations (GEE). FINDINGS Using data from 55,628 participants, we found AnthropoAge (c-statistic 0.772) outperformed CA (0.76) for prediction of mortality independently of comorbidities, sex, race/ethnicity, education, and lifestyle; this result was replicated in most countries individually except for Mexico. Individuals with accelerated aging had a ∼39% higher risk of death, and AnthropoAge also identified trends of faster biological aging per year. In longitudinal analyses, higher AnthropoAgeAccel values were independently predictive of self-reported health deterioration and new-onset deficits in basic/instrumental activities of daily living (ADL/IADL), diabetes, hypertension, cancer, chronic lung disease, myocardial infarction, and stroke. CONCLUSIONS AnthropoAge is a robust and reproducible BA metric associated with age-related outcomes. Its implementation could facilitate modeling trends of biological aging acceleration in different populations, although recalibration may enhance its utility in underrepresented populations such as individuals from Latin America.

Importance: There is limited population-based evidence on the prevalence of cognitive impairment in Mexico, a country with a rapidly aging population and where key risk factors, such as diabetes and obesity, are common. Objective: To describe the distribution of cognitive impairment in a sample of adults from Mexico City. Design, Setting, and Participants: This cross-sectional population-based study included participants from the Mexico City Prospective Study which 50,000 men and 100,000 women aged ≥35 years from two districts in 1998-2004. In 2015-2019 about 10,000 survivors were resurveyed with identical information from the original survey and additional assessments including a cognitive assessment. The main analyses included those aged 50-89 years with complete cognitive assessment and covariate data at resurvey. Main outcomes and measures: Cognition was assessed using the Mini Mental State Examination (MMSE) and those with cognitive impairment (MMSE ≤24) were identified. The distribution of MMSE scores and cognitive impairment by age, sex, and major disease risk factors (diabetes, hypertension, and adiposity) was analyzed among those with complete MMSE data and some degree of self-reported formal education. Results: Of the 9,288 participants aged 50-89 years at the 2015-2019 resurvey with complete data, 8,197 reported having at least some years of formal education. Among these (mean age 66 years; 31% men), their mean MMSE score was 26.2 (SD 3.6) points, 1,941 (24%) had cognitive impairment, mean body-mass index (BMI) was 28.6 (SD 5.5) kg/m ² , 3,008 (37%) had previously-diagnosed hypertension and 2,467 (30%) had previously-diagnosed diabetes. The sex- and district-standardised prevalence of cognitive impairment increased strongly with age, from 10% in those 50-59 years to 55% in those aged 80-89. At any given age, the prevalence of cognitive impairment was higher in women than in men. After accounting for the effects of age, sex, and district there was little difference in the prevalence of cognitive impairment between participants with or without diabetes, hypertension, overweight or obesity (BMI ≥25 km/m ² ), or high levels of fat mass. Conclusion and relevance: In this population of adults aged 50-89 years from two districts of Mexico City, the prevalence of cognitive impairment was high, particularly among women. The extent to which cognitive impairment relates to health outcomes in this population needs to be investigated. KEY POINTS: Question: What is the distribution of cognitive impairment among adults in Mexico City? Findings: In this cross-sectional study of 8,197 adults aged 50-89 years, the sex- and district-standardised prevalence of cognitive impairment ranged from 10% in those 50-59 years to 55% in those aged 80-89 and at any given age was higher in women than in men. There was little difference in the prevalence of cognitive impairment between participants with or without hypertension, diabetes or excess of adiposity. Meaning: Cognitive impairment is common in adults in Mexico City. Its relevance to major morbidity and mortality deserves future research.

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.