Blood test breakthrough pinpoints 70 proteins linked to asthma risk in major genetic study

By Dr. Chinta SidharthanReviewed by Susha Cheriyedath, M.Sc.Apr 7 2025

A large-scale proteogenomic study uncovers key proteins and immune pathways that may drive asthma risk and severity—paving the way for targeted, personalized therapies.

Study: Integration of biobank-scale genetics and plasma proteomics reveals evidence for causal processes in asthma risk and heterogeneity. Image Credit: vectorfusionart / Shutterstock

Can one blood test someday inform personalized asthma treatment?

Millions live with asthma, yet the symptoms vary significantly from person to person, and its etiology remains poorly understood.

In a recent study published in the journal Cell Genomics, a team of scientists from the biotechnology corporation Genentech Inc. in the United States used data from the United Kingdom (U.K.) Biobank to explore the intricate link between genetics, protein levels, and asthma. They identified 70 proteins—identified using genetically predicted protein levels (GPPLs), including known drug targets like IL-4R and novel candidates like GCHFR—with potential causal roles in asthma, shedding light on novel therapeutic targets and disease mechanisms.

Asthma research

Asthma affects over 260 million people worldwide, yet its biological complexity remains only partially understood. This chronic respiratory disease is not the same for everyone — it varies widely in symptoms, severity, and response to treatment. Genetics, environmental exposures, and immune responses all influence the development and progression of asthma.

Previous studies have identified many genetic variants associated with asthma and have mapped hundreds of proteins involved in inflammation and immune pathways. Nonetheless, there remains a major gap in understanding how genes and circulating proteins work together to influence asthma risk and its diverse symptoms.

Furthermore, while genome-wide association studies (GWAS) and proteomic technologies have progressed separately, integrating them to pinpoint causal biological pathways in asthma has proven challenging. This disconnect leaves many unanswered questions about the mechanisms underlying asthma's variability and resistance to treatment.

About the study

To explore how genetic variation influences asthma through protein pathways, the research team from Genentech analyzed genetic and plasma protein data from over 46,000 participants of European ancestry in the U.K. Biobank Pharma Proteomics Project (UKB-PPP).

To ensure specificity, the study categorized participants into asthma cases and controls, excluding those with other lung conditions. The researchers then used plasma samples to measure protein levels and examine the genetic factors influencing these protein levels, aiming to understand the molecular underpinnings of asthma.

The study employed a genetic causal inference framework using cis/trans protein quantitative trait loci (pQTLs), which link genetic variants to protein levels. This approach allowed the team to identify proteins whose genetically predicted levels were associated with asthma risk. To identify potential biomarkers, the researchers also conducted differential abundance analysis to identify proteins whose levels differed significantly between asthma cases and controls.

Major findings

The results indicated that genetically predicted levels of 70 proteins—54 associated through cis+trans pQTLs, 10 through overlapping signals, and 6 identified using only cis-pQTLs—were associated with asthma risk, suggesting a potential causal role for these proteins in the development of the condition. These proteins included some already known to be related to asthma, confirming previous findings, as well as novel candidates like TDRKH and CLEC7A, opening new avenues for research.

The researchers also identified 85 proteins whose levels appear to be a consequence of asthma and could serve as downstream biomarkers reflecting the disease state or progression. Examination of the genetic factors influencing protein levels also revealed a genetically mediated Toll-like receptor 1 (TLR1)-interleukin (IL)-27 axis involved in asthma risk, implicating a key inflammatory pathway.

The study also highlighted the role of the protein tetraspanin 8 (TSPAN8) in neutrophil counts, specifically in asthma patients, indicating a disease-specific link to immune cell activity. Moreover, the researchers observed that some proteins were associated with variations in asthma presentation. For example, lower TLR1 levels correlated with earlier disease onset, while others were tied to blood eosinophil counts. These associations were identified through Mendelian randomization and colocalization analyses, providing stronger evidence for causality. This suggests that distinct biological mechanisms may drive heterogeneity in asthma, opening the door to more personalized treatment strategies in the future.

While these findings were promising, the authors also acknowledged several limitations to their study. These included the inability to analyze specific asthma subtypes (e.g., Th2-high vs. Th2-low inflammation), which could exhibit distinct protein profiles, and the study’s European ancestry focus, which limits the generalizability of the findings to other populations.

Conclusions

Overall, the study provided new insights into the biological pathways that contribute to asthma risk and diversity. By integrating genetic and proteomic data from large cohorts, the researchers identified proteins that may drive the development and heterogeneity of asthma, including both established drug targets and novel candidates. Importantly, many proteins implicated as causal drivers were not differentially abundant in cases versus controls, underscoring the value of using genetically informed approaches to distinguish drivers from downstream effects. The findings may open new avenues for therapeutic development and a deeper understanding of the mechanisms underlying asthma.