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Populations are often divided categorically into distinct racial/ethnic groups based on social rather than biological constructs. Genetic ancestry has been suggested as an alternative to this categorization. Herein, we typed over 450,000 CpG sites in whole blood of 573 individuals of diverse Hispanic origin who also had high-density genotype data. We found that both self-identified ethnicity and genetically determined ancestry were each significantly associated with methylation levels at 916 and 194 CpGs, respectively, and that shared genomic ancestry accounted for a median of 75.7% (IQR 45.8% to 92%) of the variance in methylation associated with ethnicity. There was a significant enrichment (p=4.2×10 -64 ) of ethnicity-associated sites amongst loci previously associated environmental exposures, particularly maternal smoking during pregnancy. We conclude that differential methylation between ethnic groups is partially explained by the shared genetic ancestry but that environmental factors not captured by ancestry significantly contribute to variation in methylation. Whether a person develops a particular disease can depend on both genetic and environmental factors. Many studies have found that people of different races and ethnicities have different likelihoods of acquiring certain diseases. Race and ethnicity are social constructs; that is, they are not necessarily defined biologically. However, shared ancestry will produce genetic links between members of a group. In addition, members of an ethnic group often share a culture or environment that may influence their risk of disease. For example, the ‘Mediterranean diet’ inspired by the dietary habits of Southern Italians has been shown to reduce the risk of heart disease, diabetes and cancer. The addition of chemical groups – such as methyl groups – to DNA strands can affect the activity of nearby genes. Methylation is controlled by both genetic and environmental factors, and altered patterns of DNA methylation are seen in some diseases. It is therefore an ideal biological process to study to determine how race/ethnicity and ancestry contribute to a person’s susceptibility to disease. Galanter et al. have now studied the patterns of methylation found in the blood of 573 people from diverse Latino ethnic sub-groups. The different groups displayed significantly different patterns of methylation at hundreds of locations across the genome. Genetic ancestry explained approximately 75% of the variation in methylation between the sub-groups. In addition, the methylation patterns at DNA locations known to be affected by environmental exposures – for example, by exposure to tobacco while in the womb – were disproportionately likely to be methylated differently in different sub-groups. Now that more is known about the relative effects of race/ethnicity and genetic ancestry on methylation, the next step is to apply this knowledge to disease processes. This will help us to better understand the source of health disparities across different groups of people.

Air pollution is a known asthma trigger and has been associated with short-term asthma symptoms, airway inflammation, decreased lung function, and reduced response to asthma rescue medications. To assess a causal relationship between air pollution and childhood asthma using data that address temporality by estimating air pollution exposures before the development of asthma and to establish the generalizability of the association by studying diverse racial/ethnic populations in different geographic regions. This study included Latino (n = 3,343) and African American (n = 977) participants with and without asthma from five urban regions in the mainland United States and Puerto Rico. Residential history and data from local ambient air monitoring stations were used to estimate average annual exposure to five air pollutants: ozone, nitrogen dioxide (NO₂), sulfur dioxide, particulate matter not greater than 10 μm in diameter, and particulate matter not greater than 2.5 μm in diameter. Within each region, we performed logistic regression to determine the relationship between early-life exposure to air pollutants and subsequent asthma diagnosis. A random-effects model was used to combine the region-specific effects and generate summary odds ratios for each pollutant. After adjustment for confounders, a 5-ppb increase in average NO₂ during the first year of life was associated with an odds ratio of 1.17 for physician-diagnosed asthma (95% confidence interval, 1.04-1.31). Early-life NO₂ exposure is associated with childhood asthma in Latinos and African Americans. These results add to a growing body of evidence that traffic-related pollutants may be causally related to childhood asthma.

Non-small cell lung cancer (NSCLC) accounts for the majority of lung cancer cases and is frequently diagnosed at advanced stages, leading to poor survival outcomes. Molecular analysis can identify actionable mutations, such as mesenchymal-epithelial transition (MET) exon 14 skipping mutations, which serve as therapeutic targets. Capmatinib, a selective MET tyrosine kinase inhibitor (TKI), has emerged as a promising targeted therapy for this molecular subtype. We present the case of an 83-year-old former smoker with a history of chronic obstructive pulmonary disease who was diagnosed with stage 4A metastatic lung adenocarcinoma. Molecular profiling revealed a MET exon 14 skipping mutation. The patient was initiated on capmatinib, resulting in sustained disease stability and a reduction in the lesion size over a three-year follow-up. This case highlights the clinical utility of molecular testing in NSCLC, particularly for identifying MET exon 14 alterations that guide targeted therapy. Capmatinib demonstrated durable disease control and was well tolerated, offering a viable alternative to conventional chemotherapy in an elderly patient with significant comorbidities. These findings support the integration of precision oncology into the management of advanced NSCLC and underscore the potential of MET TKIs to improve outcomes in this high-risk subgroup.

Obesity is associated with increased asthma morbidity, lower drug responsiveness to inhaled corticosteroids, and worse asthma control. However, most prior investigations on obesity and asthma control have not focused on pediatric populations, considered environmental exposures, or included minority children. To examine the association between body mass index categories and asthma control among boys and girls; and whether these associations are modified by age and race/ethnicity. Children and adolescents ages 8-19 years (n = 2,174) with asthma were recruited from the Genes-environments and Admixture in Latino Americans (GALA II) Study and the Study of African Americans, Asthma, Genes, and Environments (SAGE II). Ordinal logistic regression was used to estimate odds ratios (OR) and their confidence intervals (95% CI) for worse asthma control. In adjusted analyses, boys who were obese had a 33% greater chance of having worse asthma control than their normal-weight counterparts (OR, 1.33; 95% CI, 1.04-1.71). However, for girls this association varied with race and ethnicity (P interaction = 0.008). When compared with their normal-weight counterparts, obese African American girls (OR, 0.65; 95% CI, 0.41-1.05) were more likely to have better controlled asthma, whereas Mexican American girls had a 1.91 (95% CI, 1.12-3.28) greater odds of worse asthma control. Worse asthma control is uniformly associated with increased body mass index in boys. Among girls, the direction of this association varied with race/ethnicity.

Existing methods to ascertain small sets of markers for the identification of human population structure require prior knowledge of individual ancestry. Based on Principal Components Analysis (PCA), and recent results in theoretical computer science, we present a novel algorithm that, applied on genomewide data, selects small subsets of SNPs (PCA-correlated SNPs) to reproduce the structure found by PCA on the complete dataset, without use of ancestry information. Evaluating our method on a previously described dataset (10,805 SNPs, 11 populations), we demonstrate that a very small set of PCA-correlated SNPs can be effectively employed to assign individuals to particular continents or populations, using a simple clustering algorithm. We validate our methods on the HapMap populations and achieve perfect intercontinental differentiation with 14 PCA-correlated SNPs. The Chinese and Japanese populations can be easily differentiated using less than 100 PCA-correlated SNPs ascertained after evaluating 1.7 million SNPs from HapMap. We show that, in general, structure informative SNPs are not portable across geographic regions. However, we manage to identify a general set of 50 PCA-correlated SNPs that effectively assigns individuals to one of nine different populations. Compared to analysis with the measure of informativeness, our methods, although unsupervised, achieved similar results. We proceed to demonstrate that our algorithm can be effectively used for the analysis of admixed populations without having to trace the origin of individuals. Analyzing a Puerto Rican dataset (192 individuals, 7,257 SNPs), we show that PCA-correlated SNPs can be used to successfully predict structure and ancestry proportions. We subsequently validate these SNPs for structure identification in an independent Puerto Rican dataset. The algorithm that we introduce runs in seconds and can be easily applied on large genome-wide datasets, facilitating the identification of population substructure, stratification assessment in multi-stage whole-genome association studies, and the study of demographic history in human populations.

BackgroundSecondhand smoke (SHS) exposures have been linked to asthma-related outcomes but quantitative dose–responses using biomarkers of exposure have not been widely reported.ObjectivesAssess dose–response relationships between plasma cotinine-determined SHS exposure and asthma outcomes in minority children, a vulnerable population exposed to higher levels of SHS and under-represented in the literature.MethodsWe performed analyses in 1172 Latino and African-American children with asthma from the mainland USA and Puerto Rico. We used logistic regression to assess relationships of cotinine levels ≥0.05 ng/mL with asthma exacerbations (defined as asthma-related hospitalisations, emergency room visits or oral steroid prescription) in the previous year and asthma control. The shape of dose–response relationships was assessed using a continuous exposure variable in generalised additive logistic models with penalised splines.ResultsThe OR for experiencing asthma exacerbations in the previous year for cotinine levels ≥0.05 ng/mL, compared with <0.05 ng/mL, was 1.40 (95% CI 1.03 to 1.89), while the OR for poor asthma control was 1.53 (95% CI 1.12 to 2.13). Analyses for dose–response relationships indicated increasing odds of asthma outcomes related with increasing exposure, even at cotinine levels associated with light SHS exposures.ConclusionsExposure to SHS was associated with higher odds of asthma exacerbations and having poorly controlled asthma with an increasing dose–response even at low levels of exposure. Our results support the conclusion that there are no safe levels of SHS exposures.

Independent replication of genetic associations in complex diseases, particularly in whole-genome association studies, is critical to confirm the association. A whole-genome association study identified ORMDL3 as a promising candidate gene for asthma in white populations. Here, we attempted to confirm the role of ORMDL3 genetic variants in asthma in three ethnically diverse populations: Mexican, Puerto Rican, and African American. We used family-based analyses to test for association between seven candidate single-nucleotide polymorphisms (SNPs) in and around the ORMDL3 gene and asthma and related phenotypes in 701 Puerto Rican and Mexican parent-child trios. We also evaluated these seven SNPs and an additional ORMDL3 SNP in 264 African American subjects with asthma and 176 healthy control subjects. We found significant associations between two SNPs within ORMDL3 (rs4378650 and rs12603332) and asthma in Mexicans and African Americans (P = 0.028 and 0.001 for rs4378650 and P = 0.021 and 0.001 for rs12603332, respectively), and a trend toward association in Puerto Ricans (P = 0.076 and 0.080 for SNPs rs4378650 and rs12603332, respectively). These associations became stronger among Mexican and Puerto Rican subjects with asthma with IgE levels greater than 100 IU/ml. We did not find any association between ORMDL3 SNPs and baseline lung function or response to the bronchodilator albuterol. Our results confirm that the ORMDL3 locus is a risk factor for asthma in ethnically diverse populations. However, inconsistent SNP-level results suggest that further studies will be needed to determine the mechanism by which ORMDL3 predisposes to asthma.

Latinos are the largest minority population in the United States. Although usually classified as a single ethnic group by researchers, Latinos are heterogeneous from cultural, socioeconomic, and genetic perspectives. From a cultural and social perspective, Latinos represent a wide variety of national origins and ethnic and cultural groups, with a full spectrum of social class. From a genetic perspective, Latinos are descended from indigenous American, European, and African populations. We review the historical events that led to the formation of contemporary Latino populations and use results from recent genetic and clinical studies to illustrate the unique opportunity Latino groups offer for studying the interaction between racial, genetic, and environmental contributions to disease occurrence and drug response.

Severe early-life respiratory illnesses, particularly those caused by respiratory syncytial virus (RSV) and human rhinovirus (HRV), are strongly associated with the development of asthma in children. Puerto Rican children in particular have a strikingly high asthma burden. However, prior studies of the potential associations between early-life respiratory illnesses and asthma in Puerto Rican and other minority populations have been limited. We sought to determine whether early-life respiratory illness was associated with asthma in Puerto Rican, Mexican American, and African American children. Using a logistic regression analysis, we examined the association between early-life respiratory illnesses (report of upper respiratory infection (URI), pneumonia, bronchitis, and bronchiolitis/RSV) within the first two years of life and physician-diagnosed asthma after the age of two in a large cohort of Puerto Rican, Mexican American, and African American children. While early-life respiratory illnesses were associated with greater asthma odds in Puerto Ricans, Mexican Americans, and African Americans, these associations were stronger among Puerto Rican children. Specifically, in Puerto Ricans, the odds was 6.15 (95% CI: 4.21-9.05) if the child reported at least one of the following respiratory illness: URI, pneumonia, bronchitis or bronchiolitis. The odds were also higher in Puerto Ricans when considering these conditions separately. We observed population-specific associations between early-life respiratory illnesses and asthma, which were especially significant and stronger in Puerto Ricans. Taken together with the known high burden of RSV in Puerto Rico, our results may help explain the high burden of asthma in Puerto Ricans.

Short-acting β2-adrenergic receptor agonists (SABAs) are the most commonly prescribed asthma medications worldwide. Response to SABAs is measured as bronchodilator drug response (BDR), which varies among racial/ethnic groups in the United States. However, the genetic variation that contributes to BDR is largely undefined in African Americans with asthma. To identify genetic variants that may contribute to differences in BDR in African Americans with asthma, we performed a genome-wide association study (GWAS) of BDR in 949 African-American children with asthma, genotyped with the Axiom World Array 4 (Affymetrix, Santa Clara, CA) followed by imputation using 1000 Genomes phase III genotypes. We used linear regression models adjusting for age, sex, body mass index (BMI) and genetic ancestry to test for an association between BDR and genotype at single-nucleotide polymorphisms (SNPs). To increase power and distinguish between shared vs. population-specific associations with BDR in children with asthma, we performed a meta-analysis across 949 African Americans and 1830 Latinos (total = 2779). Finally, we performed genome-wide admixture mapping to identify regions whereby local African or European ancestry is associated with BDR in African Americans. We identified a population-specific association with an intergenic SNP on chromosome 9q21 that was significantly associated with BDR (rs73650726, p = 7.69 × 10−9). A trans-ethnic meta-analysis across African Americans and Latinos identified three additional SNPs within the intron of PRKG1 that were significantly associated with BDR (rs7903366, rs7070958 and rs7081864, p ≤ 5 × 10−8). Our results failed to replicate in three additional populations of 416 Latinos and 1615 African Americans. Our findings indicate that both population-specific and shared genetic variation contributes to differences in BDR in minority children with asthma, and that the genetic underpinnings of BDR may differ between racial/ethnic groups.