Identifying the Genetic Ancestry of the Pediatric Obesity-related Asthma Variant (rs6494395) at RPS27L

Summary/Abstract:

Obesity-related asthma (OA) is a severe asthma endotype that disproportionately affects children from minority ethnic groups. We previously identified downregulation of RPS27L (40S ribosomal protein S27-like) in CD4+ (T-helper) cells from children with OA compared to cells from healthy-weight asthma (HwA) that was associated with the C allele at the rs6494395 locus. In keeping with elevated allele frequencies in populations with Latino and African ancestries, we found a higher allele frequency of rs6494395 in Hispanic/Latino and African American children with OA. Therefore, we tested the hypothesis that rs6494395 is ancestry-specific. We performed global and local genomic ancestry analysis using the programs ADMIXTURE and RFMix, respectively, to characterize the genetic ancestry of the cohort and to identify the ancestry of the genomic region containing the variant rs6494395 in the same multi-ethnic pediatric cohort where the effect of the variant on obese-related asthma was discovered. Our results indicate that rs6494395 is of African genetic ancestry. Understanding the genetic underpinnings of pediatric OA in diverse populations can improve precision medicine approaches and address health disparities in asthma outcomes.

Introduction:

In the United States, asthma is the most common pediatric chronic respiratory illness and exhibits a wide disparity among racial and ethnic groups. Lifetime prevalence is 23.6% among Puerto Ricans and 18.1% among African Americans, significantly higher than what is observed in European Americans (9.6%) and Mexican Americans (9.5%). Additionally, asthma-related mortality is four times higher in these groups. Disease burden is also unequal: Black children are more likely to experience severe, poorly controlled asthma, and asthma-related deaths occur at roughly four times the rate in Puerto Rican and Black populations compared with White children. Compounding these disparities, the groups with the highest prevalence and mortality also tend to have the poorest responses to standard asthma pharmacotherapy [1, 2]. While these discrepancies arise from various socioeconomic and environmental factors, genetic ancestry also plays a substantial role [3]. Heritability estimates for asthma range from 36-79%, underscoring the substantial genetic component of this disease [4]. However, due to its polygenic architecture, much is still unknown about causal genetic variants and the effect of these genetic variants among individuals of admixed genetic backgrounds. The observed discrepancies in disease burden and severity among populations highlight the growing need for population-based studies involving diverse genetic backgrounds to define the contribution of ancestry and improve diagnostic and treatment strategies for children in the United States [1].

Obesity-related asthma (OA) is a severe asthma endotype that disproportionately affects children from minority ethnic groups. This condition is characterized by systemic nonatopic T-helper type 1 (Th1) cell polarization and the presence of pulmonary function deficits. In a recent 2020 multi-omics study by Rastogi et al. [3], nonatopic T-helper (Th) cell immune responses in pediatric OA were investigated using samples from Hispanic/Latino and African American children. Analysis of the transcriptome and DNA methylome of CD4+ Th cells from asthma patients identified genetic and epigenetic mechanisms influencing the cellular immune responses distinct to this asthma endotype. Comparisons between healthy-weight and obese asthma Th cells revealed differential expression and DNA methylation of genes within Rho-GTPase pathways. Among the 157 genes that were found to be differentially expressed, RPS27L (40S ribosomal protein S27-like) was downregulated in Th cells of children with OA compared to children with healthy-weight asthma (HwA). This was attributed to the non-uniform distribution of genetic variants between samples. Notably, all obese children with asthma were homozygous for rs6494395 (T>C), a single nucleotide polymorphism (SNP) in the 3’ untranslated region of RPS27L. The minor allele, more common in the Latino populations (Mexican, Peruvian, Colombian, Puerto Rican and Afro-Caribbean and African American than in European populations (British, Western European) [5, 6], was an independent predictor of lower gene expression. Given that unraveling of the genetic ancestry of pediatric obesity-associated asthma may improve our understanding of disease etiology, and may have implications for precision medicine, we investigated the genetic ancestry of the variant, rs6494395, associated with downregulation of RPS27L.

Materials and Methods:

Pediatric Asthma Study Cohort

As previously described [7], one hundred twenty African American and Hispanic/Latino children (7-11 years old) with OA (n=59) and HwA (n=61) were recruited from clinics at Children’s Hospital at Montefiore between July 2013 and August 2016. Obesity was defined as a body mass index (BMI) above the 95th percentile for age and sex. Asthma status was based on physician diagnosis confirmed in medical records. All study participants underwent pulmonary function testing according to the American Thoracic Society guidelines [8].

Genotyping and Quality Control

Genomic DNA from CD4⁺ Th cells isolated from fasting blood was genotyped using the Illumina Infinium Multi-Ethnic Genotyping Array. For analysis, biallelic SNPs from autosomes were lifted from GRCh37 to GRCh38 using CrossMap v0.6.4[9]. SNPs with minor allele frequency < 0.05 or those that did not follow Hardy-Weinberg equilibrium (p < 1e-06) or those with missing genotype rate exceeding 0.05 were excluded using Plink2 v2.00a3.3 [10]. Individuals with KING kinship coefficients greater than 0.125 were considered related and removed from the analysis. After applying these quality control filters, 606,849 SNPs from 85 individuals (n=47 HwA, n=38 OA) were retained for analysis.

Reference Panel Assembly

To generate a comprehensive global genetic reference panel, we combined genetic variants from the 1000 Genomes Project [6] (1KG), Simons Genome Diversity Project [11] (SGDP), and Human Genome Diversity Project [12], consisting of 3586 individuals from 150 populations from around the world. All variants from each reference panel aligned to GRCh38, except for SGDP samples which were lifted over from GRCh37 using CrossMap. We then merged these 3 reference panels with bcftools v1.9 [13], keeping only bi-allelic single nucleotide polymorphisms (SNPs) from autosomes for quality control and downstream analysis. SNPs with minor allele frequency < 0.05, those that did not follow Hardy-Weinberg equilibrium (p < 1e7), or those with missing genotype rate exceeding 0.05 were excluded using Plink2. Individuals with kinship coefficients greater than 0.125 were considered related and removed from the analysis. After applying these quality control filters, 3,251,968 SNPs from 3,582 individuals were retained for analysis.

Population Structure and Global Ancestry Analysis

To characterize the genetic variation within our study cohort, we merged the pediatric asthma cohort with our comprehensive reference panel (n=3,667) for a total of 3,596,503 SNPs to be used in population structure analyses. We randomly sampled 100,000 SNPs to conduct principal components analysis (PCA) with Plink2 software. These data were then used to assign global ancestry proportions with ADMIXTURE v1.3.0 [14] and visualized with Pong v1.5 [15]. We tested K=5 through K=20 groups, followed by cross-validation to estimate the optimal K groups to infer global ancestry proportions (Figure S1).

Local-Ancestry Inference

For local-ancestry inference (LAI), we selected reference individuals with ≥ 95% of their ancestry from a single subcontinental ancestry (n=1941) based on our ADMIXTURE results with K=5 (based on cross-validation error analysis (Figure S1) and chosen to be representative of the 5 superpopulations (AMR, AFR, EUR, EAS, SAS). SNPs from autosomes of these individuals were phased using ShapeIt5 without a reference panel, filtering for SNPs with MAF >0.005 [16]. We then used these SNPs as our reference for phasing SNPs from our asthma cohort, resulting in a final set of 969,555 SNPs for local ancestry inference with RFMix v2.03 [17]. These SNPs were then used as the reference to phase all autosomal SNPs for the pediatric asthma cohort. To infer the local ancestry of chromosomal segments for our cohort, we analyzed 27,770 SNPs at chromosome 15 with RFMix. Ancestry calls for rs6494395 were assigned based on the results of the Viterbi algorithm spanning chr15:63018412-63428791, which captures rs6494395 located at chr15:63148856 (Figure S2).

Results:

The Bronx is home to a highly diverse and admixed population with contributions from various ancestral backgrounds. Admixed populations often exhibit complex population structures due to historical migrations, admixture, and diverse demographic histories that may not be accurately represented by self-reported ethnicity. Therefore, we used PCA to unravel genetic ancestry-based population substructure within the pediatric asthma cohort and found distinct clusters of individuals with shared genetic ancestry. We found that most of these individuals clustered around reference samples from African and American populations (Figure 1).

Figure 1:

Population structure of the pediatric asthma cohort

1a) PCA of genotype data from 85 pediatric asthma cohort individuals and merged 1KG, SGDP, HGDP reference panels. Asthma cohort individuals are represented by blue circles. The first four principal components are shown here.

1b) ADMIXTURE analysis of pediatric asthma cohort and 1KG, SGDP, HGDP reference panel samples (k=5). Each individual is represented by a vertical stacked column of color-coded admixture proportions reflecting the genetic contribution from putative ancestral populations.

To further dissect the genetic composition of our cohort, we used ADMIXTURE [4], a model based clustering program that estimates individual global ancestry proportions based on a given number of assumed ancestral populations (K). We applied this model to our study cohort and inferred K=5 to be optimal for assigning continent level genetic ancestry. ADMIXTURE results show that most pediatric asthma cohort members share ancestral components seen in African, European, and American genetic backgrounds (Figure 1b). Two individuals displayed 2-way admixture between African (blue) and South Asian (purple) ancestry, while one individual showed majority East Asian ancestry (brown) and potential admixture with African or American ancestries.

To discern the ancestral origin of the variant rs6494395 associated with pediatric obesity-related asthma, we inferred the continental ancestry of chromosomal segments of our cohort with RFMix v2 [17]. All individuals homozygous for the minor allele (n=2) were assigned African genetic ancestry for the window (chr15: 63,050,430-63,274,503) spanning rs6494395 on both haplotypes (Figure 2). For individuals heterozygous for rs6494395, we observed most of the ancestry calls were also for African ancestry (n=9), while a subset was assigned American (n=3), and 1 for European. However, the two homozygous individuals came from only African genetic backgrounds.

Figure 2:

Local-ancestry inference for rs6494394 with RFMix v2 after phasing with ShapeIt5 shows that rs6494395 originates from an African genetic background. Ancestral populations were assigned based on RFMix v2 Viterbi algorithm results spanning chr15: 63,050,430 - 63,274,503.

Discussion

The results of this follow-up study on the RPS27L variant rs6494395 underscore the critical role of genetic ancestry in understanding the etiology of pediatric obesity-related asthma. Here, we describe insights into genetic factors that contribute to this condition in an admixed population from the Bronx, highlighting the methods used to conduct these analyses. The local ancestry inference for the region containing rs6494395 using RFMix indicated that this SNP is predominantly of African genetic ancestry whereby individuals homozygous for rs6494395 were consistently assigned African ancestry for the chromosomal segment spanning the SNP. This finding adds a crucial genetic component to the well-documented higher burden of asthma among children of African-American and admixed Hispanic/Latino ancestry.

Obesity further shapes this risk landscape.

In a recent multi-omic endotyping study of 89 African-American and Hispanic/Latino children with asthma, Thompson et al. demonstrated that obesity-related metabolic and nutrient alterations accounted for up to 50% of lung-function variance [18]. Immunologic profiling also aligns with this picture. As reviewed by Rastogi (2020), pediatric obesity related asthma manifests in a neutrophilic, Th1-skewed, corticosteroid-insensitive phenotype [19]. Extending those insights, single-cell transcriptomic analyses identified a CDC42-high Th1 CD4⁺ subset uniquely expanded in obese asthma and correlated with reduced FEV₁/FVC [20]. Since RPS27L stabilizes p53 up-stream of p53/CDC42 signaling [21, 22], the African-specific haplotype containing rs6494395 provides a potential genetic link between continental ancestry, adiposity, and Th1-dominant airway inflammation. Our ancestry-specific findings highlight a SNP which impacts asthma most clearly in the context of high adiposity.

The identification of rs6494395 as an African ancestry variant underscores the necessity of including diverse populations in genetic studies to uncover variants specific to certain ancestries that contribute to disease risk. The disproportionate burden of pediatric asthma among minority ethnic groups, particularly those of African and Hispanic/Latino descent, is well-documented. As highlighted by González Burchard and Borrell [1], there is a critical need for racial and ethnic diversity in asthma precision medicine. The current underrepresentation of minority groups in genetic research limits our understanding of the full spectrum of genetic diversity and its impact on health outcomes. This study reinforces the importance of including diverse populations to ensure that the benefits of precision medicine are equitably distributed and that all patients receive the most effective and personalized care. Future research should aim to replicate these findings in larger cohorts and explore the functional implications of rs6494395 in the context of OA. Additionally, studies should investigate the interaction between genetic variants and environmental factors, as these interactions are likely to influence disease presentation and progression. In conclusion, this study demonstrates the utility of genetic ancestry analysis in uncovering the genetic factors underlying pediatric OA. The identification of rs6494395 as a variant of African ancestry adds to the development of more effective, personalized approaches to pediatric asthma management.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.