
Genetic Heterogeneity in Chronic Rhinosinusitis: A Conversation with Dr. Omar Ahmed

Omar G. Ahmed, MD
The standard chronic rhinosinusitis (CRS) treatment ladder — topical therapies, antibiotics, steroids, surgery and now biologics — has helped many patients. But it has also revealed its own ceiling.
As Dr. Omar G. Ahmed, a rhinologist and skull base surgeon at Houston Methodist, points out: There are still significant gaps in understanding CRS despite many years of treating and managing the condition.
“Our understanding of the disease is still naive,” Dr. Ahmed says, adding that this is in part due to the clinical algorithms considering CRS as a single condition, rather than a spectrum of biologically distinct disorders. This oversimplification has clinical consequences: variable treatment response, unpredictable recurrence and limited precision in selecting advanced therapies.
We spoke with Dr. Ahmed about his work to better understand the unresolved questions in CRS research and treatment, and how these insights could ultimately inform clinical care.
The missing layer: genetic diversity across populations
A major gap in CRS research, Dr. Ahmed argues, is the lack of genetic diversity in existing datasets.
“A lot of our genetic work has all been done on a homogenous population being mainly Caucasians,” he explains. Yet phenotype differences across racial groups — particularly in nasal polyposis — suggest underlying genetic variation.
His team’s goal is to characterize race-specific genetic signatures that may influence CRS susceptibility, phenotype and treatment response.
Leveraging whole-genome data at scale
Using the NIH's All of Us Research Program database, which includes more than 30,000 CRS patients, Dr. Ahmed’s group analyzed whole-genome sequencing data across racial cohorts.
Early findings from more than 6,000 patients reveal distinct mutation patterns by race — many previously undescribed. Across all groups, the unifying theme is heterogeneity. CRS is not a single disease but a genetically diverse set of disorders.
Caucasian cohort
A mutation in a gene involved in ciliary structure and motility emerged as a potential contributor to mucus stasis and chronic inflammation. “There may be a mutation in that actual structure that may be leading to some of the CRS,” Dr. Ahmed says.
African-American cohort
Variants affecting collagen type I and extracellular matrix remodeling may predispose to fibrosis and polypoid disease. Additional alterations in intracellular trafficking and stress response proteins suggest possible immune dysregulation.
Hispanic cohort
Mutations were identified in vascular permeability and inflammatory signaling pathways, including those related to vascular endothelial growth factor (VEGF). Additional findings included ciliary motility genes and lipid metabolism-related variants that may influence inflammatory cascades.
Asian cohort
Distinct phenotypes in nasal polyposis — observed both in global literature and in Houston Methodist’s own Asian American cohort — point toward unique genetic drivers.
A baseline risk factor for SNP-driven susceptibility
What influences a person chance of developing CRS? The team’s focus on single-nucleotide polymorphisms (SNPs) underscores the role of inherited susceptibility.
“Some of it’s just genetic. Some people are more susceptible to it,” Dr. Ahmed explains. Yet genotype does not always equal phenotype, complicating prediction and management.
This reinforces the need to consider CRS as a condition shaped by both genetic predisposition and environmental or immunologic triggers.
Clinical implications: toward precision rhinology
The ultimate goal is to translate these genetic insights into actionable clinical strategies. Dr. Ahmed anticipates that these findings will factor into how clinicians end up treating CRS.
- Potential future applications include:
- Biomarker-guided selection of biologics
- Risk stratification for polyp recurrence post-surgery
- Targeted therapies aimed at ciliary function, ECM remodeling or vascular signaling
- Race-specific treatment algorithms