ArticleNature communications2024
Multi-omics in nasal epithelium reveals three axes of dysregulation for asthma risk in the African Diaspora populations.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed.
- Platelet-derived serotonin epigenetically programs macrophage alternative activation to orchestrate type 2 airway inflammation.Cellular & molecular immunology · 2026Article
- Post-genome-wide association study variant-to-function challenges in asthma research.The Journal of allergy and clinical immunology · 2026Review
- Dual-transcriptomic analysis of human nasal transcriptome and microbiome reveals host-bacteria associations in symptomatic respiratory infection.BMC genomics · 2026Article
- Pathway-level epigenetic modeling illuminates the methylation architecture to asthma risk across tissues.Epigenetics & chromatin · 2026Article
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- Article
- Identification and validation of paraptosis-related biomarkers in recurrent miscarriage.Frontiers in immunology · 2025Article
- Airborne fine particulate matter exposure induces transcriptomic alterations resembling asthmatic signatures: insights from integrated omics analysis.Environmental epigenetics · 2024Article
Corrections and comments
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Authors and funding
37 authors.
Funding
Abstract
Asthma has striking disparities across ancestral groups, but the molecular underpinning of these differences is poorly understood and minimally studied. A goal of the Consortium on Asthma among African-ancestry Populations in the Americas (CAAPA) is to understand multi-omic signatures of asthma focusing on populations of African ancestry. RNASeq and DNA methylation data are generated from nasal epithelium including cases (current asthma, N = 253) and controls (never-asthma, N = 283) from 7 different geographic sites to identify differentially expressed genes (DEGs) and gene networks. We identify 389 DEGs; the top DEG, FN1, was downregulated in cases (q = 3.26 × 10
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Registered trials
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