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[Preprint]. 2025 Feb 17:2025.02.11.25322088.
doi: 10.1101/2025.02.11.25322088.

Integration of functional genomics and statistical fine-mapping systematically characterizes adult-onset and childhood-onset asthma genetic associations

Affiliations

Integration of functional genomics and statistical fine-mapping systematically characterizes adult-onset and childhood-onset asthma genetic associations

Xiaoyuan Zhong et al. medRxiv. .

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Abstract

Background: Genome-wide association studies (GWAS) have identified hundreds of loci underlying adult-onset asthma (AOA) and childhood-onset asthma (COA). However, the causal variants, regulatory elements, and effector genes at these loci are largely unknown.

Methods: We performed heritability enrichment analysis to determine relevant cell types for AOA and COA, respectively. Next, we fine-mapped putative causal variants at AOA and COA loci. To improve the resolution of fine-mapping, we integrated ATAC-seq data in blood and lung cell types to annotate variants in candidate cis-regulatory elements (CREs). We then computationally prioritized candidate CREs underlying asthma risk, experimentally assessed their enhancer activity by massively parallel reporter assay (MPRA) in bronchial epithelial cells (BECs) and further validated a subset by luciferase assays. Combining chromatin interaction data and expression quantitative trait loci, we nominated genes targeted by candidate CREs and prioritized effector genes for AOA and COA.

Results: Heritability enrichment analysis suggested a shared role of immune cells in the development of both AOA and COA while highlighting the distinct contribution of lung structural cells in COA. Functional fine-mapping uncovered 21 and 67 credible sets for AOA and COA, respectively, with only 16% shared between the two. Notably, one-third of the loci contained multiple credible sets. Our CRE prioritization strategy nominated 62 and 169 candidate CREs for AOA and COA, respectively. Over 60% of these candidate CREs showed open chromatin in multiple cell lineages, suggesting their potential pleiotropic effects in different cell types. Furthermore, COA candidate CREs were enriched for enhancers experimentally validated by MPRA in BECs. The prioritized effector genes included many genes involved in immune and inflammatory responses. Notably, multiple genes, including TNFSF4, a drug target undergoing clinical trials, were supported by two independent GWAS signals, indicating widespread allelic heterogeneity. Four out of six selected candidate CREs demonstrated allele-specific regulatory properties in luciferase assays in BECs.

Conclusions: We present a comprehensive characterization of causal variants, regulatory elements, and effector genes underlying AOA and COA genetics. Our results supported a distinct genetic basis between AOA and COA and highlighted regulatory complexity at many GWAS loci marked by both extensive pleiotropy and allelic heterogeneity.

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Conflict of interest statement

Competing interests The authors declare that they have no competing interests.

Figures

Fig. 1.
Fig. 1.
Study workflow. For each step, the input data and assay are shown in brackets. UKB: UK Biobank, OCR: open chromatin region, CRE: cis-regulatory element, MPRA: massively parallel reporter assay, eQTL: expression quantitative trait locus.
Fig. 2.
Fig. 2.
A. Heritability enrichment estimates for OCRs in asthma-relevant cell types. Lymphoid: lung B cells, lung T cells, lung NK cells, blood B cells, blood T cells, blood NK cells; Myeloid: lung macrophage, blood myeloid dendritic cells, blood plasmacytoid dendritic cells, blood monocytes; Epithelial: alveolar type 1 cells, alveolar type 2 cells, pulmonary neuroendocrine cells, lung basal cells, lung ciliated cells, lung club cells, BECs; Mesenchymal: lung matrix fibroblasts, lung myofibroblasts, lung pericytes, ASMCs; Endothelial: lung arterial cells, lung capillary cells, lung lymphatic cells. Confidence intervals are ± 2 standard errors. B. PIPs for SNPs in adult-onset asthma (left panel) and childhood-onset asthma (right panel) fine-mapping, with SNPs weighted by functional annotations (y-axis) or by uniform weights (x-axis). C. Distribution of the number of SNPs in the adult-onset asthma and childhood-onset asthma credible sets. D. Distribution of the number of shared and specific credible sets.
Fig. 3.
Fig. 3.
A. Cellular contexts of adult-onset asthma credible sets based on OCRs. The proportion of the total PIP in each credible set is attributed to OCRs of each of the five cell lineages or to none. Each horizontal bar corresponds to a credible set, which is labelled in parentheses by the nearest gene to the SNP with the highest PIP; the length of bars of different colors shows the proportion of PIPs assigned to each lineage. Because not all SNPs in the credible sets overlapped with an OCR, some were not assigned to a cell lineage (gray bars). B. Cellular context of childhood-onset asthma credible sets. C. Adult-onset asthma and childhood-onset asthma candidate CRE ePIP distributions. D. Distribution of the number of cell lineages underlying candidate CREs. E. Adult-onset asthma and childhood-onset asthma ePIP distributions of candidate CREs (from panels C and D) that overlapped with bronchial epithelial cells MPRA+ and MPRA sequences. The p-values were computed using Wilcoxon rank-sum test.
Fig. 4.
Fig. 4.
A. Adult-onset asthma high-confidence candidate causal genes (N = 10), listed in descending order. The intensity of color shows the score contributed by each category. Nearest: variants whose nearest gene is the candidate gene; ABC: variants linked to the candidate gene by the ABC model; PCHi-C: variants linked to the candidate gene by PCHi-C; eQTL: variants linked to the candidate gene by eQTL; Exon: variants in the candidate gene’s exonic regions. The number in the parentheses indicates the number of variants linked to the corresponding gene. B. Childhood-onset asthma high-confidence candidate causal genes (N = 35), listed in descending order. C. Top Biological Processes GO terms enriched among AOA (top) and COA (bottom) high-confidence candidate causal genes, generated by WebGestalt’s weighted set cover algorithm.
Fig. 5.
Fig. 5.
A. A childhood-onset asthma-specific locus at chromosome 1q25.1. From top to bottom, the first two tracks show the −log10 p-values from GWAS and PIPs from fine-mapping, respectively. Each point is a SNP, and assayed SNPs are denoted by larger squares. Different colors are used in the PIP track to represent different LD blocks. The two SNPs in candidate enhancers, rs78037977 and rs11811856, are highlighted in red. The next five tracks display chromatin accessibility from (sn)ATAC-seq of different cell lineages, with each dark blue vertical bar showing the location of an OCR. The next three tracks show chromatin interactions from PCHi-C of different cells, where the loops from the distal candidate enhancer to TNFSF4 promoter in all three cell types are highlighted in red. The last track shows the genes at the locus. BICs: blood immune cells, ASMCs: airway smooth muscle cells, BECs: bronchial epithelial cells. B. A COA-specific locus at chromosome 19q13.11. The PCHi-C loops from the candidate enhancer to the CEBPA promoter in blood cells and bronchial epithelial cells are highlighted in red.
Fig. 6.
Fig. 6.
A. A shared locus at chromosome 5q31.1. See Fig. 5 figure legend. The PCHi-C loop from the candidate enhancer to IRF1 promoter is highlighted in red in blood immune cells. B. A shared locus at chromosome 12q13.2.

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