Biomedical subjects

Carole Ober

Publications and source records attributed to Carole Ober.

6 recordsLinked to original sources

PubMed2026

Genome-wide association study of asthma with high treatment burden and/or worse outcomes defined using electronic healthcare data in UK Biobank.

BACKGROUND: In ∼10% of asthma patients, symptoms remain uncontrolled despite maximal treatment, representing an unmet clinical need. The causal variants, genes and pathways underlying genetic risk factors have not been fully elucidated, and it is unclear whether there are unique genetic risk factors for this asthma subtype. METHODS: We used electronic healthcare records linked to UK Biobank to identify asthma patients with high treatment burden and/or worse outcomes. We performed a genome-wide association study (GWAS) with this case population and healthy controls. We sought replication for associated (p≤5×10-6) signals in four independent studies (12 152 cases and 32 316 controls). Replicated signals were fine-mapped and linked to genes and pathways. RESULTS: In total, 7681 participants met our case definition and showed enrichment for adult-onset asthma, female gender and higher body mass index compared to asthma individuals not meeting case criteria. GWAS with 7681 cases and 38 405 controls revealed 21 reproducible association signals that had previously been associated with asthma, but had a larger effect size in our study. Variant-to-gene mapping highlighted 85 candidate genes, five of which were considered high confidence (BACH2, D2HGDH, IL1RL1, RPS26, SMAD3). CONCLUSION: We present the first use of electronic healthcare records in UK Biobank to identify a subtype of asthma enriched for patients with high treatment burden and/or worse outcomes. Our findings support the role of known asthma genes, highlighting genetic risk variants with stronger effect in these groups of patients. The prioritised genes provide potential therapeutic opportunities for this difficult-to-treat patient population.

Journal Article↗

PubMed2026

Post-genome-wide association study variant-to-function challenges in asthma research.

Genome-wide association studies of asthma have identified nearly 200 independent loci, yet the mechanisms through which individual loci influence asthma risk remain largely unknown. A growing array of computational and experimental tools has begun to fill these gaps by identifying causal variants and effector genes and characterizing their functions. In parallel, emerging studies are exploring the translational applications of genetic and multiomics data in asthma, including defining molecular endotypes and predicting disease risk. Here we review the strengths and limitations of current approaches for addressing the post-genome-wide association study challenges and discuss the next tier of questions and directions for the field.

Humans↗

PubMed2026

Upper airway microbiome interacts with GSDMB and ORMDL3 asthma risk SNPs to influence early-life wheeze risk.

BACKGROUND: Single-nucleotide polymorphisms (SNPs) in the chromosome 17q12-q21 region and, independently, early-life nasal microbiota dominated by Moraxella, Streptococcus, or Haemophilus (MSH) increase risk of chronic wheeze and asthma development. OBJECTIVE: We sought to determine whether 17q12-q21 risk SNPs and nasal microbiota interact to modulate childhood wheeze risk. METHODS: Nasal wash samples from 12-month-old infants in 2 birth cohorts, COAST (Childhood Origins of Asthma; n = 180) and URECA (Urban Environment and Childhood Asthma; n = 139), underwent 16S ribosomal RNA variable region 4 sequencing. Nasal microbiota dominated by MSH or Corynebacterium, Dolosigranulum, Staphylococcus, or Bacillus (CDSB) were assessed. Paired blood was genotyped for 9 17q12-q21 risk SNPs. Logistic regression tested interactions between 17q12-q21 SNPs and MSH or CDSB on wheeze risk in the first 3 years of life. A549 lung epithelial cells, CRISPR-edited to encode the rs7216389 risk genotype (rs7216389TT) were compared to the heterozygous (rs7216389CT) line using bulk RNA sequencing. RESULTS: SNPs, particularly those in the ORMDL3 (rs8076131; odds ratio [OR]: 1.72; 95% CI: 1.09-2.71; Pint = .031) and GSDMB (rs2305480; OR: 1.72; 95% CI: 1.09-2.71; Pint = 0.042; and rs7216389; OR: 1.73; 95% CI: 1.09-2.70; Pint = .047) genes, interact with MSH microbiota to increase early-life wheeze risk (false discovery rate Pint = .016 for all), while interactions with CDSB reduce risk. A549 airway epithelial cells homozygous for rs7216389TT exhibited decreased expression of genes involved in antimicrobial responses and neutrophil recruitment and evidence increased microbial adherence compared with the heterozygous cell line. CONCLUSION: Airway microbiota interact with SNPs at the 17q12-q21 locus in genes involved in sphingolipid metabolism and intracellular antimicrobial responses, to modulate wheeze risk.

Humans↗

PubMed2025

Cumulative Genetic Risk for Asthma Contributes to Disease Severity in Children with Asthma living in Urban Environments.

BACKGROUND: Childhood-onset asthma is highly heritable, with nearly 200 risk loci identified in genome-wide association studies. Aggregated polygenic risk scores can be used to quantify genetic predisposition to asthma, but their power to predict asthma severity in multi-ancestral groups has not been determined. OBJECTIVE: Our aim was to examine the predictive power of biobank-derived asthma polygenic risk scores in children with asthma living in urban environments. METHODS: We generated polygenic risk scores for asthma, derived from a large-scale genome-wide association meta-analysis, in four multi-ancestry asthma study cohorts of children living in urban environments. We assessed genetic predictions across different subphenotypes of asthma and tested for associations between genetic asthma risk and measures of asthma severity. RESULTS: Genetic asthma prediction was significantly stronger for more symptomatic asthma phenotypes (P<0.001). Polygenic risk scores were significantly higher in difficult-to-control vs. easy-to-control asthma (P=0.02). Genetic risk was also significantly associated with more frequent exacerbations (P=0.03), higher blood eosinophil levels (P=0.01), and lower lung function (P<0.001). CONCLUSION: Cumulative genetic risk for asthma is associated with disease severity and exacerbation risk in children with asthma living in urban environments.

Journal Article↗

PubMed2024

Rhinovirus infection of airway epithelial cells uncovers the non-ciliated subset as a likely driver of genetic risk to childhood-onset asthma.

Asthma is a complex disease caused by genetic and environmental factors. Studies show that wheezing during rhinovirus infection correlates with childhood asthma development. Over 150 non-coding risk variants for asthma have been identified, many affecting gene regulation in T cells, but the effects of most risk variants remain unknown. We hypothesized that airway epithelial cells could also mediate genetic susceptibility to asthma given they are the first line of defense against respiratory viruses and allergens. We integrated genetic data with transcriptomics of airway epithelial cells subject to different stimuli. We demonstrate that rhinovirus infection significantly upregulates childhood-onset asthma-associated genes, particularly in non-ciliated cells. This enrichment is also observed with influenza infection but not with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or cytokine activation. Overall, our results suggest that rhinovirus infection is an environmental factor that interacts with genetic risk factors through non-ciliated airway epithelial cells to drive childhood-onset asthma.

Humans↗

PubMed2024

Rhinovirus infection of airway epithelial cells uncovers the non-ciliated subset as a likely driver of genetic susceptibility to childhood-onset asthma.

Asthma is a complex disease caused by genetic and environmental factors. Epidemiological studies have shown that in children, wheezing during rhinovirus infection (a cause of the common cold) is associated with asthma development during childhood. This has led scientists to hypothesize there could be a causal relationship between rhinovirus infection and asthma or that RV-induced wheezing identifies individuals at increased risk for asthma development. However, not all children who wheeze when they have a cold develop asthma. Genome-wide association studies (GWAS) have identified hundreds of genetic variants contributing to asthma susceptibility, with the vast majority of likely causal variants being non-coding. Integrative analyses with transcriptomic and epigenomic datasets have indicated that T cells drive asthma risk, which has been supported by mouse studies. However, the datasets ascertained in these integrative analyses lack airway epithelial cells. Furthermore, large-scale transcriptomic T cell studies have not identified the regulatory effects of most non-coding risk variants in asthma GWAS, indicating there could be additional cell types harboring these "missing regulatory effects". Given that airway epithelial cells are the first line of defense against rhinovirus, we hypothesized they could be mediators of genetic susceptibility to asthma. Here we integrate GWAS data with transcriptomic datasets of airway epithelial cells subject to stimuli that could induce activation states relevant to asthma. We demonstrate that epithelial cultures infected with rhinovirus significantly upregulate childhood-onset asthma-associated genes. We show that this upregulation occurs specifically in non-ciliated epithelial cells. This enrichment for genes in asthma risk loci, or 'asthma heritability enrichment' is also significant for epithelial genes upregulated with influenza infection, but not with SARS-CoV-2 infection or cytokine activation. Additionally, cells from patients with asthma showed a stronger heritability enrichment compared to cells from healthy individuals. Overall, our results suggest that rhinovirus infection is an environmental factor that interacts with genetic risk factors through non-ciliated airway epithelial cells to drive childhood-onset asthma.

Preprint↗