OmegaQuant Wins NIH Grant to Study Whether Blood Fatty Acid Patterns Can Predict Eye Disease Risk

OmegaQuant Analytics has received a National Institutes of Health Small Business Innovation Research (SBIR) Phase I grant to determine whether patterns of fatty acids measured in blood can help predict future risk of age-related macular degeneration (AMD) and glaucoma, 2 of the leading causes of vision loss in older adults.

The testing lab, who specializes in fatty acid testing and research, framed the project as an effort to identify eye disease risk earlier than current screening allows."

Our goal is to determine whether the fatty acid patterns we can measure in a blood sample contain information that could help identify eye disease risk years before serious vision loss occurs," Dr. Bill Harris, principal investigator, founder of OmegaQuant, and president of the Fatty Acid Research Institute (FARI), said in the announcement.¹

Why Are AMD and Glaucoma a Priority for Earlier Detection?

The 2 conditions are already a substantial public health burden. AMD affects an estimated 20 million Americans and glaucoma about 4 million, according to figures cited in OmegaQuant's announcement,¹ and the Centers for Disease Control and Prevention has projected that the overall cost of vision problems in the US, spanning AMD, glaucoma, diabetic retinopathy, cataracts, and broader vision impairment, could rise 157% to $373 billion by 2050 without more effective prevention and earlier intervention.²

Established risk factors for both conditions, including smoking, hypertension, obesity, elevated cholesterol, cardiovascular disease, diabetes, poor nutrition, sun exposure, age, sex, and genetic predisposition, are well documented, but their combined ability to predict who will develop disease remains limited, which is the gap the project aims to address.¹

What Will the Grant-Funded Research Actually Test?

The project, titled "Developing blood fatty acid-based algorithms as early predictors of macular degeneration and glaucoma: Applying machine learning to harmonized data from prospective cohort studies," is a data-harmonization and modeling effort rather than a new clinical trial.¹

Researchers will pool fatty acid measurements and eye health outcomes already collected across the 4 cohort studies, then apply machine-learning methods to look for associations between baseline red blood cell fatty acid patterns and later AMD or glaucoma diagnoses, including possible relationships to optical coherence tomography angiography measures such as retinal thickness and vessel density.

Omega-3 fatty acids have the most established research base for a possible role in eye health, but the project's stated scope also covers trans, omega-6, saturated, and monounsaturated fatty acids, whose roles are described as unclear, suggesting the researchers are testing a broader fatty acid signature rather than confirming an omega-3-specific hypothesis.¹

How Should the Supplement Industry Interpret a Phase I SBIR Award?

An SBIR Phase I grant funds feasibility work, in this case, whether harmonized cohort data and machine-learning models can produce a usable predictive signal, not a validated clinical tool, and there is no guarantee the project will advance to Phase II or ultimately yield a marketable test or supported health claim.

The research also relies on existing observational cohort data rather than a purpose-built prospective trial, meaning any associations the models identify will need prospective validation before they could support diagnostic or labeling claims.

References

1. OmegaQuant awarded NIH grant to investigate fatty acid biomarkers for age-related macular degeneration and glaucoma. OmegaQuant. August 27, 2026. Accessed August 28, 2026. https://omegaquant.com/omegaquant-awarded-nih-grant-to-investigate-fatty-acid-biomarkers-for-age-related-macular-degeneration-and-glaucoma/

2. Looking ahead: improving our vision for the future. Centers for Disease Control and Prevention. May 15, 2024. Accessed August 28, 2026. https://archive.cdc.gov/www_cdc_gov/vision-health/data-research/vision-loss-facts/improving-vision-for-future.html